Proceedings of the 21st ACM international conference on Multimedia最新文献_第7页

Analysis and forecasting of trending topics in online media streams 在线媒体流中趋势话题的分析和预测

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502117

Tim Althoff, Damian Borth, Jörn Hees, A. Dengel

{"title":"Analysis and forecasting of trending topics in online media streams","authors":"Tim Althoff, Damian Borth, Jörn Hees, A. Dengel","doi":"10.1145/2502081.2502117","DOIUrl":"https://doi.org/10.1145/2502081.2502117","url":null,"abstract":"Among the vast information available on the web, social media streams capture what people currently pay attention to and how they feel about certain topics. Awareness of such trending topics plays a crucial role in multimedia systems such as trend aware recommendation and automatic vocabulary selection for video concept detection systems. Correctly utilizing trending topics requires a better understanding of their various characteristics in different social media streams. To this end, we present the first comprehensive study across three major online and social media streams, Twitter, Google, and Wikipedia, covering thousands of trending topics during an observation period of an entire year. Our results indicate that depending on one's requirements one does not necessarily have to turn to Twitter for information about current events and that some media streams strongly emphasize content of specific categories. As our second key contribution, we further present a novel approach for the challenging task of forecasting the life cycle of trending topics in the very moment they emerge. Our fully automated approach is based on a nearest neighbor forecasting technique exploiting our assumption that semantically similar topics exhibit similar behavior. We demonstrate on a large-scale dataset of Wikipedia page view statistics that forecasts by the proposed approach are about 9-48k views closer to the actual viewing statistics compared to baseline methods and achieve a mean average percentage error of 45-19% for time periods of up to 14 days.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73911376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 48

Towards a comprehensive computational model foraesthetic assessment of videos 面向视频审美评价的综合计算模型

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2508119

Subhabrata Bhattacharya, Behnaz Nojavanasghari, Tao Chen, Dong Liu, Shih-Fu Chang, M. Shah

{"title":"Towards a comprehensive computational model foraesthetic assessment of videos","authors":"Subhabrata Bhattacharya, Behnaz Nojavanasghari, Tao Chen, Dong Liu, Shih-Fu Chang, M. Shah","doi":"10.1145/2502081.2508119","DOIUrl":"https://doi.org/10.1145/2502081.2508119","url":null,"abstract":"In this paper we propose a novel aesthetic model emphasizing psycho-visual statistics extracted from multiple levels in contrast to earlier approaches that rely only on descriptors suited for image recognition or based on photographic principles. At the lowest level, we determine dark-channel, sharpness and eye-sensitivity statistics over rectangular cells within a frame. At the next level, we extract Sentibank features (1,200 pre-trained visual classifiers) on a given frame, that invoke specific sentiments such as \"colorful clouds\", \"smiling face\" etc. and collect the classifier responses as frame-level statistics. At the topmost level, we extract trajectories from video shots. Using viewer's fixation priors, the trajectories are labeled as foreground, and background/camera on which statistics are computed. Additionally, spatio-temporal local binary patterns are computed that capture texture variations in a given shot. Classifiers are trained on individual feature representations independently. On thorough evaluation of 9 different types of features, we select the best features from each level -- dark channel, affect and camera motion statistics. Next, corresponding classifier scores are integrated in a sophisticated low-rank fusion framework to improve the final prediction scores. Our approach demonstrates strong correlation with human prediction on 1,000 broadcast quality videos released by NHK as an aesthetic evaluation dataset.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74239577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 67

Using quadratic programming to estimate feature relevance in structural analyses of music 用二次规划估计音乐结构分析中的特征相关性

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502124

Jordan B. L. Smith, E. Chew

{"title":"Using quadratic programming to estimate feature relevance in structural analyses of music","authors":"Jordan B. L. Smith, E. Chew","doi":"10.1145/2502081.2502124","DOIUrl":"https://doi.org/10.1145/2502081.2502124","url":null,"abstract":"To identify repeated patterns and contrasting sections in music, it is common to use self-similarity matrices (SSMs) to visualize and estimate structure. We introduce a novel application for SSMs derived from audio recordings: using them to learn about the potential reasoning behind a listener's annotation. We use SSMs generated by musically-motivated audio features at various timescales to represent contributions to a structural annotation. Since a listener's attention can shift among musical features (e.g., rhythm, timbre, and harmony) throughout a piece, we further break down the SSMs into section-wise components and use quadratic programming (QP) to minimize the distance between a linear sum of these components and the annotated description. We posit that the optimal section-wise weights on the feature components may indicate the features to which a listener attended when annotating a piece, and thus may help us to understand why two listeners disagreed about a piece's structure. We discuss some examples that substantiate the claim that feature relevance varies throughout a piece, using our method to investigate differences between listeners' interpretations, and lastly propose some variations on our method.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83020444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Session details: Annotation 会话详细信息:

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/3245300

Pablo Caesar

引用次数: 0

Exploring discriminative pose sub-patterns for effective action classification 探索有效动作分类的判别姿势子模式

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502094

Xu Zhao, Yuncai Liu, Yun Fu

{"title":"Exploring discriminative pose sub-patterns for effective action classification","authors":"Xu Zhao, Yuncai Liu, Yun Fu","doi":"10.1145/2502081.2502094","DOIUrl":"https://doi.org/10.1145/2502081.2502094","url":null,"abstract":"Articulated configuration of human body parts is an essential representation of human motion, therefore is well suited for classifying human actions. In this work, we propose a novel approach to exploring the discriminative pose sub-patterns for effective action classification. These pose sub-patterns are extracted from a predefined set of 3D poses represented by hierarchical motion angles. The basic idea is motivated by the two observations: (1) There exist representative sub-patterns in each action class, from which the action class can be easily differentiated. (2) These sub-patterns frequently appear in the action class. By constructing a connection between frequent sub-patterns and the discriminative measure, we develop the SSPI, namely, the Support Sub-Pattern Induced learning algorithm for simultaneous feature selection and feature learning. Based on the algorithm, discriminative pose sub-patterns can be identified and used as a series of \"magnetic centers\" on the surface of normalized super-sphere for feature transform. The \"attractive forces\" from the sub-patterns determine the direction and step-length of the transform. This transformation makes a feature more discriminative while maintaining dimensionality invariance. Comprehensive experimental studies conducted on a large scale motion capture dataset demonstrate the effectiveness of the proposed approach for action classification and the superior performance over the state-of-the-art techniques.","PeriodicalId":20448,"journal":{"name":"Proceedings of the 21st ACM international conference on Multimedia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84524232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Querying for video events by semantic signatures from few examples 基于语义签名查询视频事件的几个例子

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502160

M. Mazloom, A. Habibian, Cees G. M. Snoek

引用次数: 47

Lecture video segmentation by automatically analyzing the synchronized slides 讲座视频分割，自动分析同步幻灯片

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2508115

Xiaoyin Che, Haojin Yang, C. Meinel

引用次数: 42

Tell me what happened here in history 告诉我历史上这里发生了什么

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502272

Jia Chen, Qin Jin, Weipeng Zhang, Shenghua Bao, Zhong Su, Yong Yu

引用次数: 2

Competitive affective gaming: winning with a smile 竞争情感游戏:用微笑取胜

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502115

André Mourão, João Magalhães

引用次数: 31

Background subtraction via coherent trajectory decomposition 通过相干轨迹分解进行背景减法

Proceedings of the 21st ACM international conference on Multimedia Pub Date : 2013-10-21 DOI: 10.1145/2502081.2502144

Zhixiang Ren, L. Chia, D. Rajan, Shenghua Gao

引用次数: 6