text:
@inproceedings{10.1145/3246389,
author = {Babaguchi, Noboru},
title = {Session Details: Plenary Talk 1},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246389},
doi = {10.1145/3246389},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393349,
author = {Fujita, Masahiro},
title = {Future Direction of Digital Content: 20th Anniversary Keynote Talk},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393349},
doi = {10.1145/2393347.2393349},
abstract = {We review the history and trends of multimedia technologies, especially focusing on audio & video products. Our lifestyles have been changing according to the developments of these technologies. We forecast the direction of multimedia technologies and our lifestyles in future. We can guess that the future direction of audio & video is going to higher and higher fidelity. Display devices will be larger and flexible. In addition, wearable devices will be popular as consumer products. It will be achieved by printing manufacture technologies. These devices and high fidelity content will realize immersive super reality.While we will enjoy the traditional audio & video content with the immersive super reality, we will use more social media by which realtime & global human-human interaction will be realized. We will be able to utilize other people's knowledge and decisions in realtime using the interactive & immersive super reality.In addition to the social networks with humans, sensor & actuator networks will also be globally established. This will extend our perception and decision abilities. We will find new problems with the distributed sensor & actuator networks, which we did not find with our ordinary perceptions. Using interactive & immersive super reality, we will collaboratively solve personal daily problems as well as global problems.Thus, in future we will realize collaborative community with interactive & immersive super reality. In the commu- nity we will enjoy entertainment content and will solve many problems collaboratively. This community itself will be the content in the future.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {1–2},
numpages = {2},
keywords = {digital content, collaborative community, display devices, interactive & immersive super reality, social media, printing manufacture},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246390,
author = {Nahrstedt, Klara and Slaney, Malcolm},
title = {Session Details: Panel 1: 20th Anniversary Panel},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246390},
doi = {10.1145/3246390},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393351,
author = {Nahrstedt, Klara and Slaney, Malcolm},
title = {Coulda, Woulda, Shoulda: 20 Years of Multimedia Opportunities},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393351},
doi = {10.1145/2393347.2393351},
abstract = {The ACM Special Interest Group on Multimedia (SIGMM) is celebrating the 20th anniversary of establishing its premier conference, the ACM International Conference on Multimedia (ACM Multimedia). The panel "Coulda, Woulda, Shoulda" is part of the celebration at the ACM Multimedia 2012. The panelists and the audience will discuss the 20 years of multimedia opportunities that our community has seen, took upon and pushed forward to advance the state of the art.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {3–4},
numpages = {2},
keywords = {multimedia processing, multimedia information systems, information interfaces and presentation, multimedia content analysis, mobile multimedia, personal multimedia computing},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246391,
author = {Aizawa, Kiyoharu},
title = {Session Details: Plenary Talk 2},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246391},
doi = {10.1145/3246391},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393353,
author = {Kamitani, Yukiyasu},
title = {Decoding Visual Experience from the Human Brain},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393353},
doi = {10.1145/2393347.2393353},
abstract = {Brain activity can be seen as "codes" that encode mental states. Recent advances in human neuroimaging such as functional magnetic resonance imaging (fMRI) have revealed brain regions that encode specific behavior and cognition. Despite the wide-spread use of human neuroimaging, its potential to read out, or "decode", mental contents from brain activity has not been fully explored. In this talk, I present methods for decoding visual representations from fMRI activity patterns based on machine learning techniques. I show how early visual features represented in "subvoxel" neural structures could be decoded from ensemble fMRI responses. Decoding of stimulus features is extended to the method for neural mind-reading, which attempts to predict a person's subjective state using a decoder trained with unambiguous stimulus presentation. We then discuss a modular decoding approach, in which a wide variety of percepts can be decoded by combining the outputs of multiple decoder modules. On the basis of this approach, we were able to reconstruct arbitrary visual images using the decoder trained on fMRI responses to only several hundred random images. Finally, I discuss potential applications of neural decoding to brain-based communications.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {5–6},
numpages = {2},
keywords = {neural decoding, mri, machine learning, vision},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246392,
author = {Xie, Lexing and Shamma, David A. and Snoek, Cees},
title = {Session Details: Panel 2: Panel Discussion},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246392},
doi = {10.1145/3246392},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393355,
author = {Xie, Lexing and Shamma, David Ayman and Snoek, Cees},
title = {Content is Dead: Long-Live Content!},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393355},
doi = {10.1145/2393347.2393355},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {7–8},
numpages = {2},
keywords = {context, multimedia, social, content},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246393,
author = {Smith, John},
title = {Session Details: Best Paper Session},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246393},
doi = {10.1145/3246393},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393357,
author = {Liu, Heng and Mei, Tao and Luo, Jiebo and Li, Houqiang and Li, Shipeng},
title = {Finding Perfect Rendezvous on the Go: Accurate Mobile Visual Localization and Its Applications to Routing},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393357},
doi = {10.1145/2393347.2393357},
abstract = {While on the go, more and more people are using their phones to enjoy ubiquitous location-based services (LBS). One of the fundamental problems of LBS is localization. Researchers are now investigating ways to use a phone-captured image for localization as it contains more scene context information than the embedded sensors. In this paper, we present a novel approach to mobile visual localization that accurately senses geographic scene context according to the current image (typically associated with a rough GPS position). Unlike most existing visual localization methods, the proposed approach is capable of providing a complete set of more accurate parameters about the scene geo---including the actual locations of both the mobile user and perhaps more importantly the captured scene along with the viewing direction. Our approach takes advantage of advanced techniques for large-scale image retrieval and 3D model reconstruction from photos. Specifically, we first perform joint geo-visual clustering in the cloud to generate scene clusters, with each scene represented by a 3D model. The 3D scene models are then indexed using a visual vocabulary tree structure. The phone-captured image is used to retrieve the relevant scene models, then aligned with the models, and further registered to the real-world map. Our approach achieves an estimation accuracy of user location within 14 meters, viewing direction within 9 degrees, and scene location within 21 meters. Such a complete set of accurate geo-parameters can lead to various LBS applications for routing that cannot be achieved with most existing methods. In particular, we showcase three novel applications: 1) accurate self-localization, 2) collaborative localization for rendezvous routing, and 3) routing for photographing. The evaluations through user studies indicate these applications are effective for facilitating the perfect rendezvous for mobile users.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {9–18},
numpages = {10},
keywords = {location-based services, geo-tagging, scene reconstruction, mobile visual localization},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393358,
author = {Sang, Jitao and Xu, Changsheng},
title = {Right Buddy Makes the Difference: An Early Exploration of Social Relation Analysis in Multimedia Applications},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393358},
doi = {10.1145/2393347.2393358},
abstract = {Social media is becoming popular these days, where user necessarily interacts with each other to form social networks. Influence network, as one special case of social network, has been recognized as significantly impacting social activities and user decisions. We emphasize in this paper that the inter-user influence is essentially topic-sensitive, as for different tasks users tend to trust different influencers and be influenced most by them. While existing research focuses on global influence modeling and applies to text-based networks, this work investigates the problem of topic-sensitive influence modeling in the multimedia domain.We propose a multi-modal probabilistic model, considering both users' textual annotation and uploaded visual image. This model is capable of simultaneously extracting user topic distributions and topic-sensitive influence strengths. By identifying the topic-sensitive influencer, we are able to conduct applications like collective search and collaborative recommendation. A risk minimization-based general framework for personalized image search is further presented, where the image search task is transferred to measure the distance of image and personalized query language models. The framework considers the noisy tag issue and enables easy incorporation of social influence. We have conducted experiments on a large-scale Flickr dataset. Qualitative as well as quantitative evaluation results have validated the effectiveness of the topic-sensitive influencer mining model, and demonstrated the advantage of incorporating topic-sensitive influence in personalized image search and topic-based image recommendation.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {19–28},
numpages = {10},
keywords = {multimedia application, social relation analysis},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393359,
author = {Wang, Zhi and Sun, Lifeng and Chen, Xiangwen and Zhu, Wenwu and Liu, Jiangchuan and Chen, Minghua and Yang, Shiqiang},
title = {Propagation-Based Social-Aware Replication for Social Video Contents},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393359},
doi = {10.1145/2393347.2393359},
abstract = {Online social network has reshaped the way how video contents are generated, distributed and consumed on today's Internet. Given the massive number of videos generated and shared in online social networks, it has been popular for users to directly access video contents in their preferred social network services. It is intriguing to study the service provision of social video contents for global users with satisfactory quality-of-experience. In this paper, we conduct large-scale measurement of a real-world online social network system to study the propagation of the social video contents. We have summarized important characteristics from the video propagation patterns, including social locality, geographical locality and temporal locality. Motivated by the measurement insights, we propose a propagation-based social-aware replication framework using a hybrid edge-cloud and peer-assisted architecture, namely PSAR, to serve the social video contents. Our replication strategies in PSAR are based on the design of three propagation-based replication indices, including a geographic influence index and a content propagation index to guide how the edge-cloud servers backup the videos, and a social influence index to guide how peers cache the videos for their friends. By incorporating these replication indices into our system design, PSAR has significantly improved the replication performance and the video service quality. Our trace-driven experiments further demonstrate the effectiveness and superiority of PSAR, which improves the local download ratio in the edge-cloud replication by 30%, and the local cache hit ratio in the peer-assisted replication by 40%, against traditional approaches.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {29–38},
numpages = {10},
keywords = {social network, hybrid edge-cloud and P2P, video replication},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393360,
author = {Lin, Shih-Yao and Shie, Chuen-Kai and Chen, Shen-Chi and Hung, Yi-Ping},
title = {Action Recognition for Human-Marionette Interaction},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393360},
doi = {10.1145/2393347.2393360},
abstract = {In this paper, we propose a human-marionette interaction system based on a human action recognition approach for applications to interactive artistic puppetry and a mimicking-marionette game. We developed an intelligent marionette called "i-marionette" that is controlled by a sophisticated control device to achieve various human actions. Moreover, we utilized an action recognition approach to enable the i-marionette to learn and recognize complex dance movements. The idea of artistic puppetry is to present a conflict scenario between two different cultural worlds: the performer is active and represents the culture of modern technology based in the real world. In contrast, the i-marionette represents traditional culture and is passive and based in a virtual world. The active performer guides the passive i-marionette to form a space-time connection between the real world and the virtual world. The i-marionette mimics the performer's action, while the performer also mimics the i-marionette's action. The performance represents an artistic conception in which humans invent technology and the i-marionette is manipulated by human control. However, in this interactive circle, the human is implicitly affected by the i-marionette. In our mimicking-marionette game, a player mimics the i-marionette's action. Subsequently, our human action recognition system measures the action similarity between the player and the i-marionette, and our system provides a similarity score.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {39–48},
numpages = {10},
keywords = {interactive game, interactive art, human action recognition},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246394,
author = {Huet, Benoit},
title = {Session Details: Full Paper Session 1: Content-Based Image Retrieval},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246394},
doi = {10.1145/3246394},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393362,
author = {Yang, Yang and Yang, Linjun and Wu, Gangshan and Li, Shipeng},
title = {A Bag-of-Objects Retrieval Model for Web Image Search},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393362},
doi = {10.1145/2393347.2393362},
abstract = {Image search reranking has been an active research topic in recent years to boost the performance of the existing web image search engine which is mostly based on textual metadata of images. Various approaches have been proposed to rerank images for general queries and argue that, they may not necessarily be optimal for queries in specific domain, e.g., object queries, since the reranking algorithms are operated on whole images, instead of the relevant parts of images. In this paper, we propose a novel bag-of-objects retrieval model for image search reranking of object queries. Firstly, we employ a common object discovery algorithm to discover query-relevant objects from the search results returned by text-based image search engine. Then, the query and its result images are represented as a language model on the query relevant object vocabulary, based on which the ranking function can be derived. As the common object discovery is unreliable and may introduce noises, we propose to incorporate the attributes of the discovered objects, e.g., size, position, etc., into the ranking function through a linear model, and the weights on the object attributes can be learned. The experiments on two subsets of Web Queries dataset comprising object queries demonstrate that our approach can significantly outperform the existing reranking methods on object queries.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {49–58},
numpages = {10},
keywords = {bag-of-objects model, image search reranking, supervised reranking, retrieval model},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393363,
author = {Nie, Liqiang and Yan, Shuicheng and Wang, Meng and Hong, Richang and Chua, Tat-Seng},
title = {Harvesting Visual Concepts for Image Search with Complex Queries},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393363},
doi = {10.1145/2393347.2393363},
abstract = {The use of image reranking to boost retrieval performance has been found to be successful for simple queries. It is, however, less effective for complex queries due to the widened semantic gap. This paper presents a scheme to enhance web image reranking for complex queries by fully exploring the information from simple visual concepts. Given a complex query, our scheme first detects the noun-phrase based visual concepts and crawls their top ranked images from popular image search engines. Next, it constructs a heterogeneous probabilistic network to model the relatedness between the complex query and each of its crawled images. The network seamlessly integrates three layers of relationships, i.e., the semantic-level, cross-modality level as well as visual-level. These mutually reinforced layers are established among the complex query and its involved visual concepts, by harnessing the contents of images and their associated textual cues. Based on the derived relevance scores, a new ranking list is generated. Extensive evaluations on a real-world dataset demonstrate that our model is able to characterize the complex queries well and achieve promising performance as compared to the state-of-the-art methods. Based on the proposed scheme, we introduce two applications: photo-based question answering and textual news visualization. Comprehensive experiments well validate the proposed scheme.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {59–68},
numpages = {10},
keywords = {complex query, image search, news visualization, photo-based qa},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393364,
author = {Shi, Miaojing and Sun, Xinghai and Tao, Dacheng and Xu, Chao},
title = {Exploiting Visual Word Co-Occurrence for Image Retrieval},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393364},
doi = {10.1145/2393347.2393364},
abstract = {Bag-of-visual-words (BOVW) based image representation has received intense attention in recent years and has improved content based image retrieval (CBIR) significantly. BOVW does not consider the spatial correlation between visual words in natural images and thus biases the generated visual words towards noise when the corresponding visual features are not stable. In this paper, we construct a visual word co-occurrence table by exploring visual word co-occurrence extracted from small affine-invariant regions in a large collection of natural images. Based on this visual word co-occurrence table, we first present a novel high-order predictor to accelerate the generation of neighboring visual words. A co-occurrence matrix is introduced to refine the similarity measure for image ranking. Like the inverse document frequency (idf), it down-weights the contribution of the words that are less discriminative because of frequent co-occurrence. We conduct experiments on Oxford and Paris Building datasets, in which the ImageNet dataset is used to implement a large scale evaluation. Thorough experimental results suggest that our method outperforms the state-of-the-art, especially when the vocabulary size is comparatively small. In addition, our method is not much more costly than the BOVW model.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {69–78},
numpages = {10},
keywords = {bovw, co-occurrence matrix, high-order predictor},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393365,
author = {Zhang, Hanwang and Zha, Zheng-Jun and Yan, Shuicheng and Bian, Jingwen and Chua, Tat-Seng},
title = {Attribute Feedback},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393365},
doi = {10.1145/2393347.2393365},
abstract = {This work presents a new interactive Content Based Image Retrieval (CBIR) scheme, termed Attribute Feedback (AF). Unlike traditional relevance feedback purely founded on low-level visual features, the Attribute Feedback system shapes users' information needs more precisely and quickly by collecting feedbacks on intermediate level semantic attributes. At each interactive iteration, AF first determines the most informative binary attributes for feedbacks, preferring the attributes that frequently (rarely) appear in current search results but are unlikely (likely) to be users' interest. The binary attribute feedbacks are then augmented by a new type of attributes, "affinity attributes", each of which is off-line learnt to describe the distance between user's envisioned image(s) and a retrieved image with respect to the corresponding affinity attribute. Based on the feedbacks on binary and affinity attributes, the images in corpus are further re-ranked towards better fitting the users' information needs. Extensive experiments on two real-world image datasets well demonstrate the superiority of the proposed scheme over other state-of-the-art relevance feedback based CBIR solutions.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {79–88},
numpages = {10},
keywords = {attribute feedback, relevance feedback, image search},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246395,
author = {Friedland, Gerald},
title = {Session Details: Full Paper Session 2: Audio and Music},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246395},
doi = {10.1145/3246395},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393367,
author = {Wang, Ju-Chiang and Yang, Yi-Hsuan and Wang, Hsin-Min and Jeng, Shyh-Kang},
title = {The Acoustic Emotion Gaussians Model for Emotion-Based Music Annotation and Retrieval},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393367},
doi = {10.1145/2393347.2393367},
abstract = {One of the most exciting but challenging endeavors in music research is to develop a computational model that comprehends the affective content of music signals and organizes a music collection according to emotion. In this paper, we propose a novel acoustic emotion Gaussians (AEG) model that defines a proper generative process of emotion perception in music. As a generative model, AEG permits easy and straightforward interpretations of the model learning processes. To bridge the acoustic feature space and music emotion space, a set of latent feature classes, which are learned from data, is introduced to perform the end-to-end semantic mappings between the two spaces. Based on the space of latent feature classes, the AEG model is applicable to both automatic music emotion annotation and emotion-based music retrieval. To gain insights into the AEG model, we also provide illustrations of the model learning process. A comprehensive performance study is conducted to demonstrate the superior accuracy of AEG over its predecessors, using two emotion annotated music corpora MER60 and MTurk. Our results show that the AEG model outperforms the state-of-the-art methods in automatic music emotion annotation. Moreover, for the first time a quantitative evaluation of emotion-based music retrieval is reported.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {89–98},
numpages = {10},
keywords = {gaussian mixture model, computational emotion model, music retrieval, em algorithm, automatic music emotion recognition},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393368,
author = {Wang, Xinxi and Rosenblum, David and Wang, Ye},
title = {Context-Aware Mobile Music Recommendation for Daily Activities},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393368},
doi = {10.1145/2393347.2393368},
abstract = {Existing music recommendation systems rely on collaborative filtering or content-based technologies to satisfy users' long-term music playing needs. Given the popularity of mobile music devices with rich sensing and wireless communication capabilities, we present in this paper a novel approach to employ contextual information collected with mobile devices for satisfying users' short-term music playing needs. We present a probabilistic model to integrate contextual information with music content analysis to offer music recommendation for daily activities, and we present a prototype implementation of the model. Finally, we present evaluation results demonstrating good accuracy and usability of the model and prototype.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {99–108},
numpages = {10},
keywords = {music recommendation, mobile computing, sensors, context awareness, activity classification},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393369,
author = {Liu, Zimu and Feng, Yuan and Li, Baochun},
title = {MusicScore: Mobile Music Composition for Practice and Fun},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393369},
doi = {10.1145/2393347.2393369},
abstract = {In this paper, we present our design of MusicScore, a professional grade application on the iOS platform for music composition and live performance tracking, used by composers and amateurs alike. As its foundation, we have designed and implemented a high-quality music engraver, capable of real-time interactive rendering on mobile devices, as well as an intuitive user interface based on multi-touch, both built from scratch using Objective-C and Cocoa Touch. To make MusicScore appealing to the general population for their practice and fun, we have introduced a unique auditory capability to MusicScore, so that it can "listen" to and analyze live instrument performance in real time. In order to compensate for the imperfect audio sensing system on mobile devices, we have proposed a collaborative sensing solution to better capture music signals in real time. To maximize the accuracy of live progress tracking and performance evaluation using a mobile device, we have designed a collection of note detection and tempo-based note matching algorithms, using a combination of microphone and accelerometer sensors. Based on our real-world implementation of MusicScore, extensive evaluation results show that MusicScore can achieve acceptably low error ratios, even for music pieces performed by highly inexperienced players.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {109–118},
numpages = {10},
keywords = {music composition, signal processing, mobile application},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393370,
author = {Chen, Chien-nan and Chu, Cing-yu and Yeh, Su-ling and Chu, Hao-hua and Huang, Polly},
title = {Modeling the Qoe of Rate Changes in SKYPE/SILK VoIP Calls},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393370},
doi = {10.1145/2393347.2393370},
abstract = {The effective end-to-end transport of delay-sensitive voice data has long been a problem in multimedia networking. One of the major issues is determining the sending rate of real-time VoIP streams such that the user experience is maximized per unit network resource consumed. A particularly interesting complication that remains to be addressed is that the available bandwidth is often dynamic. Thus, it is unclear whether a marginal increase warrants better user experience. If a user naively tunes the sending rate to the optimum at any given opportunity, the user experience could fluctuate.To investigate the effects of magnitude and frequency of rate changes on user experience, we recruited 127 human participants to systematically score emulated Skype calls with different combinations of rate changes, including varying magnitude and frequency of rate changes. Results show that 1) the rate change frequency affects the user experience on a logarithmic scale, echoing Weber-Fechner's Law [1], 2) the effect of rate change magnitude depends on how users perceive the quality difference, and 3) this study derives a closed-form model of user perception for rate changes for Skype calls.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {119–128},
numpages = {10},
keywords = {VoIP, rate adaptation, user perception, psychophysics, QoE},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246396,
author = {Hauptmann, Alexander G.},
title = {Session Details: Full Paper Session 3: Video Applications},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246396},
doi = {10.1145/3246396},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393372,
author = {Lissermann, Roman and Olberding, Simon and Petry, Benjamin and M\"{u}hlh\"{a}user, Max and Steimle, J\"{u}rgen},
title = {PaperVideo: Interacting with Videos on Multiple Paper-like Displays},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393372},
doi = {10.1145/2393347.2393372},
abstract = {Sifting and sense-making of video collections are important tasks in many professions. In contrast to sense-making of paper documents, where physical structuring of many documents has proven to be key to effective work, interaction with video is still restricted to the traditional "one video at a time" paradigm. This paper investigates how interaction with video can benefit from paper-like displays that allow for working with multiple videos simultaneously in physical space. We present a corresponding approach and system called PaperVideo, including novel interaction concepts for both video and audio. These include spatial techniques for temporal navigation, arranging, grouping and linking of videos, as well as for managing video contents and simultaneous audio playback on multiple displays. An evaluation with users provides insights into how paper-based navigation with videos improves active video work.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {129–138},
numpages = {10},
keywords = {electronic paper, thinfilm display, tangible user interface, pile, video, flexible display, multiple displays},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393373,
author = {Saini, Mukesh Kumar and Gadde, Raghudeep and Yan, Shuicheng and Ooi, Wei Tsang},
title = {MoViMash: Online Mobile Video Mashup},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393373},
doi = {10.1145/2393347.2393373},
abstract = {With the proliferation of mobile video cameras, it is becoming easier for users to capture videos of live performances and socially share them with friends and public. As an attendee of such live performances typically has limited mobility, each video camera is able to capture only from a range of restricted viewing angles and distance, producing a rather monotonous video clip. At such performances, however, multiple video clips can be captured by different users, likely from different angles and distances. These videos can be combined to produce a more interesting and representative mashup of the live performances for broadcasting and sharing. The earlier works select video shots merely based on the quality of currently available videos. In real video editing process, however, recent selection history plays an important role in choosing future shots. In this work, we present MoViMash, a framework for automatic online video mashup that makes smooth shot transitions to cover the performance from diverse perspectives. Shot transition and shot length distributions are learned from professionally edited videos. Further, we introduce view quality assessment in the framework to filter out shaky, occluded, and tilted videos. To the best of our knowledge, this is the first attempt to incorporate history-based diversity measurement, state-based video editing rules, and view quality in automated video mashup generations. Experimental results have been provided to demonstrate the effectiveness of MoViMash framework.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {139–148},
numpages = {10},
keywords = {mobile video, virtual director, video mashup},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393374,
author = {Zhang, Zhebin and Zhou, Chen and Xin, Bo and Wang, Yizhou and Gao, Wen},
title = {An Interactive System of Stereoscopic Video Conversion},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393374},
doi = {10.1145/2393347.2393374},
abstract = {With the recent booming of 3DTV industry, more and more stereoscopic videos are demanded by the market. This paper presents a system of converting conventional monocular videos to stereoscopic ones. In this system, an input video is firstly segmented into shots to reduce operations on similar frames. Then, automatic depth estimation and interactive image segmentation are integrated to obtain depth maps and foreground/background segments on selected key frames. Within each video shot, such results are propagated from key frames to non-key frames. Combined with a depth-to-disparity conversion method, the system synthesizes the counterpart (either left or right) view for stereoscopic display by warping the original frame according to disparity maps. For evaluation, we use human labeled depth map as the reference and compute both the mean opinion score (MOS) and Peak signal-to-noise ratio (PSNR) to valuate the converted video quality. Experiment results demonstrate that the proposed conversion system and methods achieves encouraging performance.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {149–158},
numpages = {10},
keywords = {3dtv, foreground segmentation, 2d-to-3d conversion, depth estimation, depth to disparity},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393375,
author = {Kegel, Ian and Cesar, Pablo and Jansen, Jack and Bulterman, Dick C.A. and Stevens, Tim and Kort, Joke and F\"{a}rber, Nikolaus},
title = {Enabling 'togetherness' in High-Quality Domestic Video},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393375},
doi = {10.1145/2393347.2393375},
abstract = {Low-cost video conferencing systems have provided an existence proof for the value of video communication in a home setting. At the same time, current systems have a number of fundamental limitations that inhibit more general social interactions among multiple groups of participants. In our work, we describe the development, implementation and evaluation of a domestic video conferencing system that is geared to providing true 'togetherness' among conference participants. We show that such interactions require sophisticated support for high-quality audiovisual presentation, and processing support for person identification and localisation. In this paper, we describe user requirements for effective interpersonal interaction. We then report on a system that implements these requirements. We conclude with a systems and user evaluation of this work. We present results that show that participants in a video conference can be made feel as 'together' as collocated players of a board game.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {159–168},
numpages = {10},
keywords = {interaction, togetherness, social communication, video conferencing, visual composition},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246397,
author = {Ngo, Chong-Wah},
title = {Session Details: Full Paper Session 4: Large Scale Search},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246397},
doi = {10.1145/3246397},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393377,
author = {Zhou, Wengang and Lu, Yijuan and Li, Houqiang and Tian, Qi},
title = {Scalar Quantization for Large Scale Image Search},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393377},
doi = {10.1145/2393347.2393377},
abstract = {Bag-of-Words (BoW) model based on SIFT has been widely used in large scale image retrieval applications. Feature quantization plays a crucial role in BoW model, which generates visual words from the high dimensional SIFT features, so as to adapt to the inverted file structure for indexing. Traditional feature quantization approaches suffer several problems: 1) high computational cost---visual words generation (codebook construction) is time consuming especially with large amount of features; 2) limited reliability---different collections of images may produce totally different codebooks and quantization error is hard to be controlled; 3) update inefficiency--once the codebook is constructed, it is not easy to be updated. In this paper, a novel feature quantization algorithm, scalar quantization, is proposed. With scalar quantization, a SIFT feature is quantized to a descriptive and discriminative bit-vector, of which the first tens of bits are taken out as code word. Our quantizer is independent of collections of images. In addition, the result of scalar quantization naturally lends itself to adapt to the classic inverted file structure for image indexing. Moreover, the quantization error can be flexibly reduced and controlled by efficiently enumerating nearest neighbors of code words.The performance of scalar quantization has been evaluated in partial-duplicate Web image search on a database of one million images. Experiments reveal that the proposed scalar quantization achieves a relatively 42% improvement in mean average precision over the baseline (hierarchical visual vocabulary tree approach), and also outperforms the state-of-the-art Hamming Embedding approach and soft assignment method.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {169–178},
numpages = {10},
keywords = {large-scale image retrieval, sift, scalar quantization},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393378,
author = {Wang, Jingdong and Li, Shipeng},
title = {Query-Driven Iterated Neighborhood Graph Search for Large Scale Indexing},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393378},
doi = {10.1145/2393347.2393378},
abstract = {In this paper, we address the approximate nearest neighbor (ANN) search problem over large scale visual descriptors. We investigate a simple but very effective approach, neighborhood graph search, which constructs a neighborhood graph to index the data points and conducts a local search, expanding neighborhoods with a best-first manner, for ANN search. Our empirical analysis shows that neighborhood expansion is very efficient, with O(1) cost, for a new NN candidate location, and has high chances to locate true NNs and hence it usually performs well. However, it often gets sub-optimal solutions since local search only checks the neighborhood of the current solution, or conducts exhaustive and continuous neighborhood expansions to find better solutions, which deteriorates the query efficiency.In this paper, we propose a query-driven iterated neighborhood graph search approach to improve the performance. We follow the iterated local search (ILS) strategy, widely-used in combinatorial optimization, to find a solution beyond a local optimum. We handle the key challenge in making neighborhood graph search adapt to ILS, Perturbation, which generates a new pivot to restart a local search. To this end, we present a criterion to check if the local search over a neighborhood graph arrives at the local solution. Moreover, we exploit the query and search history to design the perturbation scheme, resulting in a more effective search. The major benefit is avoiding unnecessary neighborhood expansions and hence more efficiently finding true NNs. Experimental results on large scale SIFT matching, similar image search, and shape retrieval with non-metric distance measures, show that our approach performs much better than previous state-of-the-art ANN search approaches.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {179–188},
numpages = {10},
keywords = {local neighborhood graph search, ann search, iterated, query-driven},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393379,
author = {Tolias, Giorgos and Kalantidis, Yannis and Avrithis, Yannis},
title = {SymCity: Feature Selection by Symmetry for Large Scale Image Retrieval},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393379},
doi = {10.1145/2393347.2393379},
abstract = {Many problems, including feature selection, vocabulary learning, location and landmark recognition, structure from motion and 3d reconstruction, rely on a learning process that involves wide-baseline matching on multiple views of the same object or scene. In practical large scale image retrieval applications however, most images depict unique views where this idea does not apply. We exploit self-similarities, symmetries and repeating patterns to select features within a single image. We achieve the same performance compared to the full feature set with only a small fraction of its index size on a dataset of unique views of buildings or urban scenes, in the presence of one million distractors of similar nature. Our best solution is linear in the number of correspondences, with practical running times of just a few milliseconds.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {189–198},
numpages = {10},
keywords = {symmetry detection, indexing, feature selection, self-similarity, image retrieval},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393380,
author = {Liu, Zhen and Li, Houqiang and Zhou, Wengang and Tian, Qi},
title = {Embedding Spatial Context Information into Inverted Filefor Large-Scale Image Retrieval},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393380},
doi = {10.1145/2393347.2393380},
abstract = {One most popular approach for large-scale content-based image retrieval is based on the Bag-of-Visual-Words model. Since the spatial context among local features is very important for visual content identification, many approaches index local features' geometric clues, such as location, scale and orientation for post-verification. To obtain consistent accuracy performance, the amount of top ranked images that post-verification approach needs to process is proportional to the image database size. When the database is very large, the verified images will be too many to be processed in real-time response. To address this issue, in this paper, we explore two approaches to embed spatial context information into the inverted file. The first one is to build a spatial relationship dictionary embedded with spatial context among local features, which we call one-one spatial relationship method. The second one is to generate a spatial context binary signature for each feature, which we call one-multiple spatial relationship method. Then we build an inverted file with spatial information between local features. The geometric verification is implicitly achieved while traversing the inverted file. Experimental results on benchmark Holidays dataset demonstrate the efficiency of the proposed algorithm.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {199–208},
numpages = {10},
keywords = {sift, large-scale image retrieval, spatial relationship dictionary, one-multiple relationship, spatial context binary signature, feature tuple, spatial context, one-one relationship},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246398,
author = {Sebe, Nicu},
title = {Session Details: Full Paper Session 5: Person and Face Analysis},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246398},
doi = {10.1145/3246398},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393382,
author = {Dibeklio\u{g}lu, Hamdi and Gevers, Theo and Salah, Albert Ali and Valenti, Roberto},
title = {A Smile Can Reveal Your Age: Enabling Facial Dynamics in Age Estimation},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393382},
doi = {10.1145/2393347.2393382},
abstract = {Estimation of a person's age from the facial image has many applications, ranging from biometrics and access control to cosmetics and entertainment. Many image-based methods have been proposed for this problem. In this paper, we propose a method for the use of dynamic features in age estimation, and show that 1) the temporal dynamics of facial features can be used to improve image-based age estimation; 2) considered alone, static image-based features are more accurate than dynamic features. We have collected and annotated an extensive database of face videos from 400 subjects with an age range between 8 and 76, which allows us to extensively analyze the relevant aspects of the problem. The proposed system, which fuses facial appearance and expression dynamics, performs with a mean absolute error of 4.81 (4.87) years. This represents a significant improvement of accuracy in comparison to the sole use of appearance-based features.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {209–218},
numpages = {10},
keywords = {facial dynamics, age estimation},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393383,
author = {Bu, Jiajun and Xu, Bin and Wu, Chenxia and Chen, Chun and Zhu, Jianke and Cai, Deng and He, Xiaofei},
title = {Unsupervised Face-Name Association via Commute Distance},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393383},
doi = {10.1145/2393347.2393383},
abstract = {Recently, the task of unsupervised face-name association has received a considerable interests in multimedia and information retrieval communities. It is quite different with the generic facial image annotation problem because of its unsupervised and ambiguous assignment properties. Specifically, the task of face-name association should obey the following three constraints: (1) a face can only be assigned to a name appearing in its associated caption or to null; (2) a name can be assigned to at most one face; and (3) a face can be assigned to at most one name. Many conventional methods have been proposed to tackle this task while suffering from some common problems, eg, many of them are computational expensive and hard to make the null assignment decision. In this paper, we design a novel framework named face-name association via commute distance (FACD), which judges face-name and face-null assignments under a unified framework via commute distance (CD) algorithm. Then, to further speed up the on-line processing, we propose a novel anchor-based commute distance (ACD) algorithm whose main idea is using the anchor point representation structure to accelerate the eigen-decomposition of the adjacency matrix of a graph. Systematic experiment results on a large scale and real world image-caption database with a total of 194,046 detected faces and 244,725 names show that our proposed approach outperforms many state-of-the-art methods in performance. Our framework is appropriate for a large scale and real-time system.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {219–228},
numpages = {10},
keywords = {commute distance, unsupervised, face-name association},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393384,
author = {Lu, Xin and Suryanarayan, Poonam and Adams, Reginald B. and Li, Jia and Newman, Michelle G. and Wang, James Z.},
title = {On Shape and the Computability of Emotions},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393384},
doi = {10.1145/2393347.2393384},
abstract = {We investigated how shape features in natural images influence emotions aroused in human beings. Shapes and their characteristics such as roundness, angularity, simplicity, and complexity have been postulated to affect the emotional responses of human beings in the field of visual arts and psychology. However, no prior research has modeled the dimensionality of emotions aroused by roundness and angularity. Our contributions include an in depth statistical analysis to understand the relationship between shapes and emotions. Through experimental results on the International Affective Picture System (IAPS) dataset we provide evidence for the significance of roundness-angularity and simplicity-complexity on predicting emotional content in images. We combine our shape features with other state-of-the-art features to show a gain in prediction and classification accuracy. We model emotions from a dimensional perspective in order to predict valence and arousal ratings which have advantages over modeling the traditional discrete emotional categories. Finally, we distinguish images with strong emotional content from emotionally neutral images with high accuracy.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {229–238},
numpages = {10},
keywords = {shape features, psychology, human emotion},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393385,
author = {Nguyen, Tam V. and Liu, Si and Ni, Bingbing and Tan, Jun and Rui, Yong and Yan, Shuicheng},
title = {Sense Beauty via Face, Dressing, and/or Voice},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393385},
doi = {10.1145/2393347.2393385},
abstract = {Discovering the secret of beauty has been the pursuit of artists and philosophers for centuries. Nowadays, the computational model for beauty estimation has been actively explored in computer science community, yet with the focus mainly on facial features. In this work, we perform a comprehensive study of female attractiveness conveyed by single/multiple modalities of cues, i.e., face, dressing and/or voice, and aim to uncover how different modalities individually and collectively affect the human sense of beauty. To this end, we collect the first Multi-Modality Beauty (M2B) dataset in the world for female attractiveness study, which is thoroughly annotated with attractiveness levels converted from manual k-wise ratings and semantic attributes of different modalities. A novel Dual-supervised Feature-Attribute-Task (DFAT) network is proposed to jointly learn the beauty estimation models of single/multiple modalities as well as the attribute estimation models. The DFAT network differentiates itself by its supervision in both attribute and task layers. Several interesting beauty-sense observations over single/multiple modalities are reported, and the extensive experimental evaluations on the collected M2B dataset well demonstrate the effectiveness of the proposed DFAT network for female attractiveness estimation.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {239–248},
numpages = {10},
keywords = {dressing, attributes, dual-supervised feature-attribute-task network, {face, voice} attractiveness},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246399,
author = {Venkatasubrahanian, Nalini},
title = {Session Details: Full Paper Session 6: Video Distribution},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246399},
doi = {10.1145/3246399},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393387,
author = {Shen, Haiying and Li, Ze and Wang, Hailang and Li, Jin},
title = {Leveraging Social Network Concepts for Efficient Peer-to-Peer Live Streaming Systems},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393387},
doi = {10.1145/2393347.2393387},
abstract = {In current peer-to-peer (P2P) live streaming systems, nodes in a channel form a P2P overlay for video sharing. To watch a new channel, a node depends on the centralized server to join in the overlay of the channel. The increase in the number of channels in today's live streaming applications triggers users' desire of watching multiple channels successively or simultaneously. However, the support of such watching modes in current applications is no better than joining in different channel overlays successively or simultaneously, which if widely used, poses heavy burden on the centralized server. In order to achieve higher efficiency and scalability, we propose a Social network-Aided efficient liVe strEaming system (SAVE). SAVE regards users' channel switching or multi-channel watching as interactions between channels. By collecting the information of channel interactions and nodes' interests and watching times, SAVE forms nodes in multiple channels with frequent interactions into an overlay, constructs bridges between overlays of channels with less frequent interactions, and enables nodes to identify friends sharing similar interests and watching times. Thus, a node can connect to a new channel while staying in its current overlay, using bridges or relying on its friends, reducing the need to contact the centralized server. Extensive experimental results from the PeerSim simulator and PlanetLab verify that SAVE outperforms other popular protocols in system efficiency and server load reduction.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {249–258},
numpages = {10},
keywords = {P2P live streaming, P2P networks, social networks},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393388,
author = {Feng, Yuan and Li, Baochun and Li, Bo},
title = {Jetway: Minimizing Costs on Inter-Datacenter Video Traffic},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393388},
doi = {10.1145/2393347.2393388},
abstract = {It is typical for video streaming service providers (such as NetFlix) to rely on services from cloud providers (such as Amazon), in order to build a scalable video streaming platform with high availability. The trend is largely driven by the fact that cloud providers deploy a number of datacenters inter-connected by high-capacity links, spanning different geographical regions. Video traffic across datacenters, such as video replication and transit server-to-customer video serving, constitutes a large portion of a cloud provider's inter-datacenter traffic. Charged by ISPs, such inter-datacenter video traffic incurs substantial operational costs to a cloud provider. In this paper, we argue that costs incurred by such inter-datacenter video traffic can be reduced or even minimized by carefully choosing paths, and by assigning flow rates on each inter-datacenter link along every path. We present Jetway, a new set of algorithms designed to minimize cloud providers' operational costs on inter-datacenter video traffic, by optimally routing video flows in an online fashion. Algorithms in Jetway are designed by following a methodical approach based on an in-depth theoretical analysis. As a highlight of this paper, we have built a real-world system framework to implement and deploy Jetway in the Amazon EC2 datacenters. With both simulations and real-world experiments using our implementation, we show that Jetway effectively helps transmitting videos across datacenters with reduced costs to cloud providers and satisfactory real-world performance.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {259–268},
numpages = {10},
keywords = {flow optimization, inter-datacenter traffic},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393389,
author = {Changuel, Nesrine and Sayadi, Bessem and Kieffer, Michel},
title = {Control of Distributed Servers for Quality-Fair Delivery of Multiple Video Streams},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393389},
doi = {10.1145/2393347.2393389},
abstract = {This paper proposes a quality-fair video delivery system able to transmit several encoded video streams to mobile users sharing some wireless resource. Video quality fairness, as well as similar delivery delay is targeted among streams. The proposed control system is implemented within some aggregator located near the bottleneck of the network.This is done by allocating the transmission rate among streams based on the quality of the already encoded and buffered packets in the aggregator. Encoding rate targets are evaluated by the aggregator and fed back to each remote video server, or directly evaluated by each server in a distributed way. Each encoding rate target is adjusted for each stream independently based on the corresponding buffering delay in the aggregator.The transmission and encoding rate control problems are addressed with a control-theoretic perspective. The system is described with a multi-input multi-output model and several Proportional Integral (PI) controllers are used to adjust the video quality as well as the buffering delay. The study of the system equilibrium and stability provides guidelines for choosing the parameters of the PI controllers. Experimental results show that better quality fairness is obtained compared to classical transmission rate fair streaming solutions while keeping similar buffering delays.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {269–278},
numpages = {10},
keywords = {distributed systems, video, control design},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393390,
author = {Li, Xin and Dong, Mian and Ma, Zhan and Fernandes, Felix C.A.},
title = {GreenTube: Power Optimization for Mobile Videostreaming via Dynamic Cache Management},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393390},
doi = {10.1145/2393347.2393390},
abstract = {Mobile video streaming has become one of the most popular applications in the trend of smartphone booming and the prevalence of 3G/4G networks, i.e., HSPA, HSPA+, and LTE. However, the prohibitively high power consumption by 3G/4G radios in smartphones reduces battery life significantly and thus severely hurts user experience. To tackle this challenge, we designed GreenTube, a system that optimizes power consumption for mobile video streaming by judiciously scheduling downloading activities to minimize unnecessary active periods of 3G/4G radio. GreenTube achieves this by dynamically managing the downloading cache based on user viewing history and network condition. We implemented GreenTube on Android-based smartphones. Experimental results show that GreenTube achieves large power reductions of more than 70% (on the 3G/4G radio) and 40% (for the whole system). We believe GreenTube is a desirable upgrade to the Android system, especially in the light of increasing LTE popularity.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {279–288},
numpages = {10},
keywords = {mobile video streaming, power optimization},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246400,
author = {Tian, Qi},
title = {Session Details: Full Paper Session 7: Visual Search},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246400},
doi = {10.1145/3246400},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393392,
author = {Worring, Marcel and Engl, Andreas and Smeria, Camelia},
title = {A Multimedia Analytics Framework for Browsing Image Collections in Digital Forensics},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393392},
doi = {10.1145/2393347.2393392},
abstract = {Searching through large collections of images to find patterns of use or to find sets of relevant items is difficult, especially when the information to consider is not only the content of the images itself, but also the associated metadata. Multimedia analytics is a new approach to such problems. We consider the case of forensic experts facing image collections of growing size during digital forensic investigations. We answer the forensic challenge by developing specialised novel interactive visualisations which employ content-based image clusters in both the analysis as well as in all visualizations. Their synergy makes the task of manually browsing these collections more effective and efficient. Evaluation of such multimedia analytics is a notoriously hard problem as there are so many factors influencing the result. As a controlled evaluation, we developed a user simulation framework to create image collections with time and directory information as metadata. We apply it in a number of scenarios to illustrate its use. The simulation tool is available to other researchers via our website.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {289–298},
numpages = {10},
keywords = {visual analytics, information visualization, image search},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393393,
author = {Cao, Liangliang and Li, Zhenguo and Mu, Yadong and Chang, Shih-Fu},
title = {Submodular Video Hashing: A Unified Framework towards Video Pooling and Indexing},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393393},
doi = {10.1145/2393347.2393393},
abstract = {This paper develops a novel framework for efficient large-scale video retrieval. We aim to find video according to higher level similarities, which is beyond the scope of traditional near duplicate search. Following the popular hashing technique we employ compact binary codes to facilitate nearest neighbor search. Unlike the previous methods which capitalize on only one type of hash code for retrieval, this paper combines heterogeneous hash codes to effectively describe the diverse and multi-scale visual contents in videos. Our method integrates feature pooling and hashing in a single framework. In the pooling stage, we cast video frames into a set of pre-specified components, which capture a variety of semantics of video contents. In the hashing stage, we represent each video component as a compact hash code, and combine multiple hash codes into hash tables for effective search. To speed up the retrieval while retaining most informative codes, we propose a graph-based influence maximization method to bridge the pooling and hashing stages. We show that the influence maximization problem is submodular, which allows a greedy optimization method to achieve a nearly optimal solution. Our method works very efficiently, retrieving thousands of video clips from TRECVID dataset in about 0.001 second. For a larger scale synthetic dataset with 1M samples, it uses less than 1 second in response to 100 queries. Our method is extensively evaluated in both unsupervised and supervised scenarios, and the results on TRECVID Multimedia Event Detection and Columbia Consumer Video datasets demonstrate the success of our proposed technique.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {299–308},
numpages = {10},
keywords = {submodular, video hashing, indexing, multiple feature hashing, feature pooling},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393394,
author = {Castanon, Gregory D. and Caron, Andre Louis and Saligrama, Venkatesh and Jodoin, Pierre-marc},
title = {Exploratory Search of Long Surveillance Videos},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393394},
doi = {10.1145/2393347.2393394},
abstract = {We present a fast and flexible content-based retrieval method for surveillance video. Designing a video search robust to uncertain activity duration, high variability in object shapes and scene content is challenging. We propose a two-step approach to video search. First, local features are inserted into an inverted index using locality-sensitive hashing (LSH). Second, we utilize a novel dynamic programming (DP) approach to robustify against temporal distortion, limited obscuration and imperfect queries. DP exploits causality to assemble the local features stored in the index into a video segment which matches the query video. Pre-processing of archival video is performed in real-time, and retrieval speed scales as a function of the number of matches rather than video length. We derive bounds on the rate of false positives, demonstrate the effectiveness of the approach for counting, motion pattern recognition and abandoned object applications using seven challenging video datasets and compare with existing work.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {309–318},
numpages = {10},
keywords = {surveillance, dynamic programming, exploratory search, video search},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393395,
author = {Kofler, Christoph and Yang, Linjun and Larson, Martha and Mei, Tao and Hanjalic, Alan and Li, Shipeng},
title = {When Video Search Goes Wrong: Predicting Query Failure Using Search Engine Logs and Visual Search Results},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393395},
doi = {10.1145/2393347.2393395},
abstract = {The recent increase in the volume and variety of video content available online presents growing challenges for video search. Users face increased difficulty in formulating effective queries and search engines must deploy highly effective algorithms to provide relevant results. Although lately much effort has been invested in optimizing video search engine results, relatively little attention has been given to predicting for which queries results optimization is most useful, i.e., predicting which queries will fail. Being able to predict when a video search query would fail is likely to make the video search result optimization more efficient and effective, improve the search experience for the user by providing support in the query formulation process and in this way boost the development of video search engines in general. While insight about a query's performance in general could be obtained using the well-known concept of query performance prediction (QPP), we propose a novel approach for predicting a failure of a video search query in the specific context of a search session. Our 'context-aware query failure' prediction approach uses a combination of 'user indicators' and 'engine indicators' to predict whether a particular query is likely to fail in the context of a particular search session. User indicators are derived from the search log and capture the patterns of query (re)formulation behavior and the click-through data of a user during a typical video search session. Engine indicators are derived from the video search results list and capture the visual variance of search results that would be offered to the user for the given query. We validate our approach experimentally on a test set containing 1+ million video search queries and show its effectiveness compared to a set of conventional QPP baselines. Our approach achieves a 13% relative improvement over the baseline.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {319–328},
numpages = {10},
keywords = {video search, query failure, query performance prediction, visual relatedness, transaction log analysis},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246401,
author = {Nack, Frank},
title = {Session Details: Full Paper Session 8: Human-Centric Media},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246401},
doi = {10.1145/3246401},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393397,
author = {Srivastava, Ruchir and Feng, Jiashi and Roy, Sujoy and Yan, Shuicheng and Sim, Terence},
title = {Don't Ask Me What i'm like, Just Watch and Listen},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393397},
doi = {10.1145/2393347.2393397},
abstract = {Traditional (based on psychology) approaches for personality assessment of an individual require him/her to fill up a questionnaire. This paper presents a novel way of utilizing multimodal cues to automatically fill up the questionnaire. The contributions of this work are three-fold. (1) Novel psychology-based audio/visual/lexical features are proposed and shown to be effective in predicting answers to a personality questionnaire, Big-Five Inventory-10 (BFI- 10). (2) Extracted features are used to learn linear and kernel versions of a novel regression model, 'SLoT', to automatically predict BFI-10 answers. The model is based on Sparse and Low-rank Transformation (SLoT). (3) Predicted answers are used to compute personality scores using standard BFI-10 scoring scheme. We evaluated our approach on a dataset of 3907 clips (for 50 characters from movies of diverse genres) manually labeled with BFI-10 answers and personality scores as ground-truth. Experiments indicate that the proposed 'SLoT' model effectively automates the answering process by emulating human understanding. We also conclude that predicting personality scores through predicting answers first is better than directly predicting scores based on audio/visual features (as studied in state-of-the art methods).},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {329–338},
numpages = {10},
keywords = {emotion recognition, personality assessment, multimodal features, movie analysis},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393398,
author = {Poulsen, Esben Skouboe and Andersen, Hans J\o{}rgen and Jensen, Ole B. and Gade, Rikke and Thyrrestrup, Tobias and Moeslund, Thomas B.},
title = {Controlling Urban Lighting by Human Motion Patterns Results from a Full Scale Experiment},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393398},
doi = {10.1145/2393347.2393398},
abstract = {This paper presents a full-scale experiment investigating the use of human motion intensities as input for interactive illumination of a town square in the city of Aalborg in Denmark. As illuminators sixteen 3.5 meter high RGB LED lamps were used. The activity on the square was monitored by three thermal cameras and analysed by computer vision software from which motion intensity maps and peoples trajectories were estimated and used as input to control the interactive illumination. The paper introduces a 2-layered interactive light strategy addressing ambient and effect illumination criteria totally four light scenarios were designed and tested. The result shows that in general people immersed in the street lighting did not notice that the light changed according to their presence or actions, but people watching from the edge of the square noticed the interaction between the illumination and the immersed persons. The experiment also demonstrated that interactive can give significant power savings. In the current experiment there was a difference of 92% between the most and less energy consuming light scenario.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {339–348},
numpages = {10},
keywords = {urban lighting, responsive light design, urban light design, interactive illumination},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393399,
author = {Yanulevskaya, Victoria and Uijlings, Jasper and Bruni, Elia and Sartori, Andreza and Zamboni, Elisa and Bacci, Francesca and Melcher, David and Sebe, Nicu},
title = {In the Eye of the Beholder: Employing Statistical Analysis and Eye Tracking for Analyzing Abstract Paintings},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393399},
doi = {10.1145/2393347.2393399},
abstract = {Most artworks are explicitly created to evoke a strong emotional response. During the centuries there were several art movements which employed different techniques to achieve emotional expressions conveyed by artworks. Yet people were always consistently able to read the emotional messages even from the most abstract paintings. Can a machine learn what makes an artwork emotional? In this work, we consider a set of 500 abstract paintings from Museum of Modern and Contemporary Art of Trento and Rovereto (MART), where each painting was scored as carrying a positive or negative response on a Likert scale of 1-7. We employ a state-of-the-art recognition system to learn which statistical patterns are associated with positive and negative emotions. Additionally, we dissect the classification machinery to determine which parts of an image evokes what emotions. This opens new opportunities to research why a specific painting is perceived as emotional. We also demonstrate how quantification of evidence for positive and negative emotions can be used to predict the way in which people observe paintings.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {349–358},
numpages = {10},
keywords = {emotion recognition, visual art, abstract paintings, eye tracking},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393400,
author = {Xu, Qianqian and Huang, Qingming and Yao, Yuan},
title = {Online Crowdsourcing Subjective Image Quality Assessment},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393400},
doi = {10.1145/2393347.2393400},
abstract = {Recently, HodgeRank on random graphs has been proposed as an effective framework for multimedia quality assessment problem based on paired comparison method. With the random design on large graphs, it is particularly suitable for large scale crowdsourcing experiments on Internet. However, to make it more practical toward this purpose, it is necessary to develop online algorithms to deal with sequential or streaming data. In this paper, we propose an online rating scheme based on HodgeRank on random graphs, to assess image quality when assessors and image pairs enter the system in a sequential way in a crowdsourceable scenario. The scheme is shown in both theory and experiments to be effective by exhibiting similar performance to batch learning under the Erd\"{o}s-R\'{e}nyi random graph model for sampling. It enables us to derive global rating and monitor intrinsic inconsistency in the real time. We demonstrate the effectiveness of the proposed framework on LIVE and IVC databases.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {359–368},
numpages = {10},
keywords = {topology evolution, paired comparison, hodgerank, triangular curl, online, crowdsourcing, random graphs, subjective image quality assessment, persistent homology},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246402,
author = {Shen, Heng Tao},
title = {Session Details: Full Paper Session 9: Presentation and Organization},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246402},
doi = {10.1145/3246402},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393402,
author = {Gupta, Raj Kumar and Chia, Alex Yong-Sang and Rajan, Deepu and Ng, Ee Sin and Zhiyong, Huang},
title = {Image Colorization Using Similar Images},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393402},
doi = {10.1145/2393347.2393402},
abstract = {We present a new example-based method to colorize a gray image. As input, the user needs only to supply a reference color image which is semantically similar to the target image. We extract features from these images at the resolution of superpixels, and exploit these features to guide the colorization process. Our use of a superpixel representation speeds up the colorization process. More importantly, it also empowers the colorizations to exhibit a much higher extent of spatial consistency in the colorization as compared to that using independent pixels. We adopt a fast cascade feature matching scheme to automatically find correspondences between superpixels of the reference and target images. Each correspondence is assigned a confidence based on the feature matching costs computed at different steps in the cascade, and high confidence correspondences are used to assign an initial set of chromatic values to the target superpixels. To further enforce the spatial coherence of these initial color assignments, we develop an image space voting framework which draws evidence from neighboring superpixels to identify and to correct invalid color assignments. Experimental results and user study on a broad range of images demonstrate that our method with a fixed set of parameters yields better colorization results as compared to existing methods.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {369–378},
numpages = {10},
keywords = {cascade feature matching, automatic colorization},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393403,
author = {Kuhna, Mikko and Kivel\"{a}, Ida-Maria and Oittinen, Pirkko},
title = {Semi-Automated Magazine Layout Using Content-Based Image Features},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393403},
doi = {10.1145/2393347.2393403},
abstract = {We present a system for automating magazine layout process and data on its performance in a user evaluation test. The purpose of the study is to find the feasibility of the key system variables on the end-user. This semi-automatic system is based on content-based image feature algorithms to automate the layout process. The image related automation includes image cropping, overlaying text on top of images, image color palette creation, and image alignment. The algorithms rely on principles of photography and are used here together in the context of graphic design. For example the rule-of-space and leading line concepts can be extended to layout contexts for improved alignment of text and images. The computation is based on automatic analysis, such as face detection, color saliency, and textureness. We used the automation to create a functional prototype, an iPad magazine, using an open HTML5 eBook framework, which relies on CSS3 media queries for the layout adaptation. User experiments (40 participants) were conducted where the system was compared against two commercial iPad magazine systems in terms of overall usability with emphasis on visual aspects. Questionnaires and free commenting was used in a task-based usage scenario. The experiments were video recorded and the user comments were transcribed and coded into attributes. Usability results mixed with qualitative observation are reported. Results show that usability, read- ability and visuality are important to the users. Our system was considered more usable than the other two systems with some of the defining aspects being simplicity in terms of usability, subjective readability and visual clarity.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {379–388},
numpages = {10},
keywords = {user evaluation, layout adaptation, responsive design, image feature, page layout},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393404,
author = {Chandra, Surendar and Biehl, Jacob T. and Boreczky, John and Carter, Scott and Rowe, Lawrence A.},
title = {Understanding Screen Contents for Building a High Performance, Real Time Screen Sharing System},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393404},
doi = {10.1145/2393347.2393404},
abstract = {Faithful sharing of screen contents is an important collaboration feature. Prior systems were designed to operate over constrained networks. They performed poorly even without such bottlenecks. To build a high performance screen sharing system, we empirically analyzed screen contents for a variety of scenarios. We showed that screen updates were sporadic with long periods of inactivity. When active, screens were updated at far higher rates than was supported by earlier systems. The mismatch was pronounced for interactive scenarios. Even during active screen updates, the number of updated pixels were frequently small. We showed that crucial information can be lost if individual updates were merged. When the available system resources could not support high capture rates, we showed ways in which updates can be effectively collapsed. We showed that Zlib lossless compression performed poorly for screen updates. By analyzing the screen pixels, we developed a practical transformation that significantly improved compression rates. Our system captured 240 updates per second while only using 4.6 Mbps for interactive scenarios. Still, while playing movies in fullscreen mode, our approach could not achieve higher capture rates than prior systems; the CPU remains the bottleneck. A system that incorporates our findings is deployed within the lab.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {389–398},
numpages = {10},
keywords = {displaycast, screencast, screen capture, screen sharing},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393405,
author = {Bhojan, Anand and Chong, Lee Kee and Chang, Ee-Chien and Chan, Mun Choon and Akkihebbal, Ananda L. and Ooi, Wei Tsang},
title = {El-Pincel: A Painter Cloud Service for Greener Web Pages},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393405},
doi = {10.1145/2393347.2393405},
abstract = {Due to their thin size, vivid colors, high contrast and power efficiency, OLED (Organic Light-Emitting Diode) display and its variants such as AMOLED (Active Matrix OLED) displays are increasingly replacing traditional LCD (Liquid Crystal Display) screens in smart phones. However, the power efficiency of OLED screens greatly depends on the luminance and colors of the displayed contents on the screen. Web browsing is one of the most widely used applications in mobile devices. In this paper, we present our cloud service, which intelligently re-paints the web pages in real-time with power efficient colors and HVS (Human Visual System) based tone mapping techniques, without adversely affecting the identity (brand color) of the web pages as well as the user's browsing experience. El-pincel helps to save up to 60% of OLED energy with color combinations that ensure good legibility and pleasing affective response to human eyes.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {399–408},
numpages = {10},
keywords = {color transformation, OLED display, browsing, low power, color harmony, cloud service, tone mapping},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246403,
author = {Nakamura, Yuichi},
title = {Session Details: Full Paper Session 10: Haptics},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246403},
doi = {10.1145/3246403},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393407,
author = {Chaudhari, Rahul and \c{C}izmeci, Burak and Kuchenbecker, Katherine J. and Choi, Seungmoon and Steinbach, Eckehard},
title = {Low Bitrate Source-Filter Model Based Compression of Vibrotactile Texture Signals in Haptic Teleoperation},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393407},
doi = {10.1145/2393347.2393407},
abstract = {Vibrotactile signals convey the touch-based characteristics of object surfaces felt through a tool. They particularly enhance the quality of human-machine interactions by providing realistic haptic perception of textures. In this paper, inspired by the similarities observed between vibrotactile texture signals and speech signals, we present a novel vibrotactile texture codec for bilateral teleoperation, based on well-known speech coding techniques. The proposed low bitrate, high quality codec preserves not only the spectral signature vital to the general feel of the texture, but also important temporal features of the texture signal. We report a compression ratio of 8:1 (12.5 %) with a constant output bitrate of 4 kbps, and we validate the perceptual transparency of the codec via rigorous subjective tests and analyses.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {409–418},
numpages = {10},
keywords = {teleoperation, haptic textures, data compression},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393408,
author = {McDaniel, Troy L. and Goldberg, Morris and Bala, Shantanu and Fakhri, Bijan and Panchanathan, Sethuraman},
title = {Vibrotactile Feedback of Motor Performance Errors for Enhancing Motor Learning},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393408},
doi = {10.1145/2393347.2393408},
abstract = {Feedback related to motor performance is integral to improving the control, timing and coordination of movements. However, motor learning traditionally occurs within a group setting, limiting the quality of instruction and feedback. Even during one-on-one instruction, there are impediments to feedback such as physical separation between trainer and trainee, common in many sports such as snowboarding and swimming. We propose an inexpensive solution for real-time vibrotactile positioning and speed feedback that can complement traditional motor learning, and is compatible with existing vibrotactile motor instructions. We present a psychophysical study that examined participants' initial reactions to feedback stimuli pertaining to position and speed adjustments. Results support the proposed design in terms of both usability and naturalness, and provide insight into participants' conceptualization of feedback signals and feedback for rotational movements.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {419–428},
numpages = {10},
keywords = {vibrotactile feedback, motor learning, instructions},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393409,
author = {Zhou, Yinsheng and Sim, Khe Chai and Tan, Patsy and Wang, Ye},
title = {MOGAT: Mobile Games with Auditory Training for Children with Cochlear Implants},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393409},
doi = {10.1145/2393347.2393409},
abstract = {Cochlear implants have improved the lives of tens of thousands of the hearing impaired by providing sufficient auditory perception for speech, but these devices are far from satisfactory for music perception. Many cochlear implant recipients, especially pre-lingually deafened children, have difficulty recognizing and producing specific pitches. To improve musical auditory habilitation for children post cochlear implantation, we developed MOGAT: MObile Games with Auditory Training. The system includes three musical games built with off-the-shelf mobile devices to train their pitch perception and intonation skills respectively, and a cloud-based web service which allows music therapists to monitor and design individual training for children. The design of the games and web service was informed by a pilot survey (N=60 children). To ensure widespread use with low-cost mobile devices, we minimized the computation load while retaining highly accurate audio analysis. A 6-week user study (N=15 children) showed that the music habilitation with MOGAT was intuitive, enjoyable and motivating. It has improved most children's pitch discrimination and production, and several children's improvement was statistically significant (p<0.05).},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {429–438},
numpages = {10},
keywords = {auditory habilitation, music, game, mobile, children, cochlear implant},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246404,
author = {Scherp, Ansgar},
title = {Session Details: Full Paper Session 11: Event Recognition},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246404},
doi = {10.1145/3246404},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393411,
author = {Weng, Ming-Fang and Lin, Yen-Yu and Tang, Nick C. and Liao, Hong-Yuan Mark},
title = {Visual Knowledge Transfer among Multiple Cameras for People Counting with Occlusion Handling},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393411},
doi = {10.1145/2393347.2393411},
abstract = {We present a framework to count the number of people in an environment where multiple cameras with different angles of view are available. We consider the visual cues captured by each camera as a knowledge source, and carry out cross-camera knowledge transfer to alleviate the difficulties of people counting, such as partial occlusions, low-quality images, clutter backgrounds, and so on. Specifically, this work distinguishes itself with the following contributions. First, we overcome the variations of multiple heterogeneous cameras with different perspective settings by matching the same groups of pedestrians taken by these cameras, and present an algorithm for accomplishing cross-camera correspondence. Second, the proposed counting model is composed of a pair of collaborative regressors. While one regressor measures people counts by the features extracted from intra-camera visual evidences, the other recovers the yielded residual by taking the conflicts among inter-camera predictions into account. The two regressors are elegantly coupled, and jointly lead to an accurate counting system. Additionally, we provide a set of manually annotated pedestrian labels on the PETS 2010 videos for performance evaluation. Our approach is comprehensively tested in various settings and compared with competitive baselines. The significant improvement in performance manifests the effectiveness of the proposed approach.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {439–448},
numpages = {10},
keywords = {people counting, correspondence estimation, transfer learning},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393412,
author = {Jiang, Lu and Hauptmann, Alexander G. and Xiang, Guang},
title = {Leveraging High-Level and Low-Level Features for Multimedia Event Detection},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393412},
doi = {10.1145/2393347.2393412},
abstract = {This paper addresses the challenge of Multimedia Event Detection by proposing a novel method for high-level and low-level features fusion based on collective classification. Generally, the method consists of three steps: training a classifier from low-level features; encoding high-level features into graphs; and diffusing the scores on the established graph to obtain the final prediction. The final prediction is derived from multiple graphs each of which corresponds to a high-level feature. The paper investigates two graph construction methods using logarithmic and exponential loss functions, respectively and two collective classification algorithms, i.e. Gibbs sampling and Markov random walk. The theoretical analysis demonstrates that the proposed method converges and is computationally scalable and the empirical analysis on TRECVID 2011 Multimedia Event Detection dataset validates its outstanding performance compared to state-of-the-art methods, with an added benefit of interpretability.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {449–458},
numpages = {10},
keywords = {collective classification, multi-modal integration, feature fusion},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393413,
author = {Miller, Chreston and Quek, Francis},
title = {Interactive Data-Driven Discovery of Temporal Behavior Models from Events in Media Streams},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393413},
doi = {10.1145/2393347.2393413},
abstract = {This paper investigates a technique for the discovery of temporal behavior models within multimedia event data. Advancements in both technology and the marketplace present us the opportunity for research in analysis of situated human behavior using video and other sensor data (media streams). By situated analysis, we mean the study of behavior in time as opposed to looking at behavior in the form of aggregated data divorced from how they occur in context. Human and social scientists seek to model behavior captured in media, and these data may be represented in a multi-dimensional event data space derived from media streams. The knowledge of these scientists (experts) is a valuable resource which can be leveraged to search this space. We propose a solution that incorporates the expert in an iteratively, interactive data-driven discovery process to evolve a desired behavior model. We test our solution's accuracy on a multimodal meeting corpus with a progressive three tiered approach.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {459–468},
numpages = {10},
keywords = {structure model learning, human-machine cooperation, model evolution, event data, temporal behavior models},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393414,
author = {Ma, Zhigang and Yang, Yi and Cai, Yang and Sebe, Nicu and Hauptmann, Alexander G.},
title = {Knowledge Adaptation for Ad Hoc Multimedia Event Detection with Few Exemplars},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393414},
doi = {10.1145/2393347.2393414},
abstract = {Multimedia event detection (MED) has a significant impact on many applications. Though video concept annotation has received much research effort, video event detection remains largely unaddressed. Current research mainly focuses on sports and news event detection or abnormality detection in surveillance videos. Our research on this topic is capable of detecting more complicated and generic events. Moreover, the curse of reality, i.e., precisely labeled multimedia content is scarce, necessitates the study on how to attain respectable detection performance using only limited positive examples. Research addressing these two aforementioned issues is still in its infancy. In light of this, we explore Ad Hoc MED, which aims to detect complicated and generic events by using few positive examples. To the best of our knowledge, our work makes the first attempt on this topic. As the information from these few positive examples is limited, we propose to infer knowledge from other multimedia resources to facilitate event detection. Experiments are performed on real-world multimedia archives consisting of several challenging events. The results show that our approach outperforms several other detection algorithms. Most notably, our algorithm outperforms SVM by 43% and 14% comparatively in Average Precision when using Gaussian and Χ2 kernel respectively.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {469–478},
numpages = {10},
keywords = {structural adaptive regression (sar), multimedia event detection (med), knowledge adaptation, ad hoc med},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246405,
author = {Xie, Lexing},
title = {Session Details: Full Paper Session 12: Semantic Tagging},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246405},
doi = {10.1145/3246405},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393416,
author = {Qi, Zhongang and Yang, Ming and Zhang, Zhongfei (Mark) and Zhang, Zhengyou},
title = {Multi-View Learning from Imperfect Tagging},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393416},
doi = {10.1145/2393347.2393416},
abstract = {In many real-world applications, tagging is imperfect: incomplete, inconsistent, and error-prone. Solutions to this problem will generate societal and technical impacts. In this paper, we investigate this arguably new problem: learning from imperfect tagging. We propose a general and effective learning scheme called the Multi-view Imperfect Tagging Learning (MITL) to this problem. The main idea of MITL lies in extracting the information of the imperfectly tagged training dataset from multiple views to differentiate the data points in the role of classification. Further, a novel discriminative classification method is proposed under the framework of MITL, which explicitly makes use of the given multiple labels simultaneously as an additional feature to deliver a more effective classification performance than the existing literature where one label is considered at a time as the classification target while the rest of the given labels are completely ignored at the same time. The proposed methods can not only complete the incomplete tagging but also denoise the noisy tagging through an inductive learning. We apply the general solution to the problem with a more specific context - imperfect image annotation, and evaluate the proposed methods on a standard dataset from the related literature. Experiments show that they are superior to the peer methods on solving the problem of learning from imperfect tagging in cross-media.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {479–488},
numpages = {10},
keywords = {multi-label space, correction and prediction, imperfect tagging, image annotation completion},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393417,
author = {Lindner, Albrecht and Shaji, Appu and Bonnier, Nicolas and S\"{u}sstrunk, Sabine},
title = {Joint Statistical Analysis of Images and Keywords with Applications in Semantic Image Enhancement},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393417},
doi = {10.1145/2393347.2393417},
abstract = {With the advent of social image-sharing communities, millions of images with associated semantic tags are now available online for free and allow us to exploit this abundant data in new ways. We present a fast non-parametric statistical framework designed to analyze a large data corpus of images and semantic tag pairs and find correspondences between image characteristics and semantic concepts. We learn the relevance of different image characteristics for thousands of keywords from one million annotated images. We demonstrate the framework's effectiveness with three different examples of semantic image enhancement: we adapt the gray-level tone-mapping, emphasize semantically relevant colors, and perform a defocus magnification for an image based on its semantic context. The performance of our algorithms is validated with psychophysical experiments.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {489–498},
numpages = {10},
keywords = {semantic image processing, image understanding, statistical analysis, large-scale experimentation, crowd sourcing},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393418,
author = {Lu, Zhiwu and Peng, Yuxin},
title = {Image Annotation by Semantic Sparse Recoding of Visual Content},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393418},
doi = {10.1145/2393347.2393418},
abstract = {This paper presents a new semantic sparse recoding method to generate more descriptive and robust representation of visual content for image annotation. Although the visual bag-of-words (BOW) representation has been reported to achieve promising results in image annotation, its visual codebook is completely learnt from low-level visual features using quantization techniques and thus the so-called semantic gap remains unbridgeable. To handle such challenging issue, we utilize both the annotations of training images and the predicted annotations of test images to improve the original visual BOW representation. This is further formulated as a sparse coding problem so that the noise issue induced by the inaccurate quantization of visual features can also be handled to some extent. By developing an efficient sparse coding algorithm, we successfully generate a new visual BOW representation for image annotation. Since such sparse coding has actually incorporated the high-level semantic information into the original visual codebook, we thus consider it as semantic sparse recoding of the visual content. Although the predicted annotations of test images are also used as inputs by the traditional image annotation refinement, we focus on the visual BOW representation refinement for image annotation in this paper. The experimental results on two benchmark datasets show the superior performance of our semantic sparse recoding method in image annotation.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {499–508},
numpages = {10},
keywords = {semantic gap, semantic sparse recoding, visual bow representation, image annotation},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393419,
author = {Wu, Fei and Yuan, Ying and Rui, Yong and Yan, Shuicheng and Zhuang, Yueting},
title = {Annotating Web Images Using NOVA: NOn-ConVex Group SpArsity},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393419},
doi = {10.1145/2393347.2393419},
abstract = {As image feature vector is large, selecting the right features plays a fundamental role in Web image annotation. Most existing approaches are either based on individual feature selection, which leads to local optima, or using a convex penalty, which leads to inconsistency. To address these difficulties, in this paper we propose a new sparsity-based approach NOVA (NOn-conVex group spArsity). To the best of our knowledge, NOVA is the first to introduce non-convex penalty for group selection in high-dimensional heterogeneous features space. Because it is a group-sparsity approach, it approximately reaches global optima. Because it uses non-convex penalty, it achieves the consistency. We demonstrate the superior performance of NOVA via three means. First, we present theoretical proof that NOVA is consistent, satisfying un-biasness, sparsity and continuity. Second, we show NOVA converges to the true underlying model by using a ground-truth-available generative-model simulation. Third, we report extensive experimental results on three diverse and widely-used data sets Kodak, MSRA-MM 2.0, and NUS-WIDE. We also compare NOVA against the state-of-the-art approaches, and report superior experimental results.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {509–518},
numpages = {10},
keywords = {group feature selection, non-convex group sparsity, consistent, image annotation},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246406,
author = {Yan, Shuicheng},
title = {Session Details: Full Paper Session 13: Image Analysis},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246406},
doi = {10.1145/3246406},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393421,
author = {Sun, Zhenbang and Wang, Changhu and Zhang, Liqing and Zhang, Lei},
title = {Query-Adaptive Shape Topic Mining for Hand-Drawn Sketch Recognition},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393421},
doi = {10.1145/2393347.2393421},
abstract = {In this work, we study the problem of hand-drawn sketch recognition. Due to large intra-class variations presented in hand-drawn sketches, most of existing work was limited to a particular domain or limited pre-defined classes. Different from existing work, we target at developing a general sketch recognition system, to recognize any semantically meaningful object that a child can recognize. To increase the recognition coverage, a web-scale clipart image collection is leveraged as the knowledge base of the recognition system. To alleviate the problems of intra-class shape variation and inter-class shape ambiguity in this unconstrained situation, a query-adaptive shape topic model is proposed to mine object topics and shape topics related to the sketch, in which, multiple layers of information such as sketch, object, shape, image, and semantic labels are modeled in a generative process. Besides sketch recognition, the proposed topic model can also be used for related applications such as sketch tagging, image tagging, and sketch-based image search. Extensive experiments on different applications show the effectiveness of the proposed topic model and the recognition system.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {519–528},
numpages = {10},
keywords = {query-adaptive shape topic model, sketch recognition, sketch-based image search},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393422,
author = {Han, Yahong and Wu, Fei and Lu, Xinyan and Tian, Qi and Zhuang, Yueting and Luo, Jiebo},
title = {Correlated Attribute Transfer with Multi-Task Graph-Guided Fusion},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393422},
doi = {10.1145/2393347.2393422},
abstract = {Due to the describable or human-nameable nature of visual attributes, the attribute-based methods have been receiving much attentions in recent years in many applications. The advantages of the utilization of visual attributes are that they can be composed to create descriptions at various levels of specificity or they can be learned once and then applied to recognize new objects or categories. Therefore, attribute prediction becomes an essential problem to boost image understanding. This paper proposes an approach for correlated attribute transfer from a well-defined source image set to an uncontrolled target image set for attribute prediction. We call it correlated attribute transfer with multi-task graph-guided fusion (CAT-MtG2F). The novelty of CAT-MtG2F is to encourage highly correlated attributes to share a common set of relevant low-level features and transfer the learned common structure from the source image set to the target image set. The experiments show that the proposed CAT-MtG2F achieves better performance in attribute prediction.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {529–538},
numpages = {10},
keywords = {attribute prediction, feature selection, transfer learning, multi-task graph-guided fusion},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393423,
author = {Xie, Lingxi and Tian, Qi and Zhang, Bo},
title = {Spatial Pooling of Heterogeneous Features for Image Applications},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393423},
doi = {10.1145/2393347.2393423},
abstract = {The Bag-of-Features (BoF) model has played an important role for image representation in many multimedia applications. It has been extensively applied to many tasks including image classification, image retrieval, scene understanding, and so on. Despite the advantages of this model such as simplicity, efficiency and generality, there are also notable drawbacks for this model, including poor power of semantic expression of local descriptors, and lack of robust structures upon single visual words. To overcome these problems, various techniques have been proposed, such as multiple descriptors, spatial context modeling and interest region detection. Though they have been proven to improve the BoF model to some extent, there still lacks a coherent scheme to integrate each individual module.To address the problems above, we propose a novel framework with spatial pooling of heterogeneous features. Our framework differs from the traditional Bag-of-Features model on three aspects. First, we propose a new scheme for combining texture and edge based local features together at the descriptor extraction level. Next, we build geometric visual phrases to model spatial context upon heterogeneous features for mid-level representation of images. Finally, based on a smoothed edgemap, a simple and effective spatial weighting scheme is performed on our mid-level image representation. We test our integrated framework on several benchmark datasets for image classification and retrieval applications. The extensive results show the superior performance of our algorithm over state-of-the-art methods.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {539–548},
numpages = {10},
keywords = {bof framework, complementary descriptors, spatial weighting, geometric visual phrases, image representation, multimedia applications, phrase pooling},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393424,
author = {Ushiku, Yoshitaka and Harada, Tatsuya and Kuniyoshi, Yasuo},
title = {Efficient Image Annotation for Automatic Sentence Generation},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393424},
doi = {10.1145/2393347.2393424},
abstract = {Sentence generation from images is an ultimate goal of image recognition. In this paper, we attack a novel problem, the "multi-keyphrase problem", to address this goal. We hypothesize that image contents can be described with multi-keyphrases, and that a natural sentence can be generated by connecting multi-keyphrases with an experimental grammar model. Existing methods require semantic knowledge such as labels of an object, action, or scene. Using these methods, we must strive to prepare a highly organized dataset. Therefore, we propose a novel online learning method for multi-keyphrase estimation. The proposed framework, although simple and scalable, can generate sentences from images with no semantic knowledge. Moreover, the proposed method for multi-keyphrase estimation is applicable to image annotation, and it achieves state-of-the-art performance. Our experiment using only images and texts demonstrates that the proposed framework is useful for sentence generation from images.},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
pages = {549–558},
numpages = {10},
keywords = {multi-stack decoding, passive-aggressive, online learning},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/3246407,
author = {Mei, Tao},
title = {Session Details: Full Paper Session 14: Mobile Systems},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3246407},
doi = {10.1145/3246407},
booktitle = {Proceedings of the 20th ACM International Conference on Multimedia},
location = {Nara, Japan},
series = {MM '12}
}

@inproceedings{10.1145/2393347.2393426,
author = {Tseng, Yu-Chuan and Huang, Yi-Ching and Wu, Kuan-Ying and Chin, Chi-Ping},
title = {Dinner of Luci\'{e}Rnaga: An Interactive Play with IPhone App in Theater},
year = {2012},
isbn = {9781450310895},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2393347.2393426},
doi = {10.1145/2393347.2393426},
abstract = {Interactive digital art in the field of performance is emerging as an increasingly

license: Unlicense

repository: goyalkaraniit/acm-cr

repo_name: goyalkaraniit/acm-cr

branch_name: refs/heads/main