By Guangyu Zhu, Shuicheng Yan, Tony X. Han, Changsheng Xu (auth.), Kuo-Tien Lee, Wen-Hsiang Tsai, Hong-Yuan Mark Liao, Tsuhan Chen, Jun-Wei Hsieh, Chien-Cheng Tseng (eds.)
This two-volume lawsuits constitutes the refereed papers of the seventeenth foreign Multimedia Modeling convention, MMM 2011, held in Taipei, Taiwan, in January 2011. The fifty one revised common papers, 25 specified consultation papers, 21 poster consultation papers, and three demo consultation papers, have been conscientiously reviewed and chosen from 450 submissions. The papers are geared up in topical sections on audio, photograph video processing, coding and compression; media content material looking and retrieval; multi-camera, multi-view, and 3D structures; multimedia indexing and mining; multimedia content material research; multimedia sign processing and communications; and multimedia purposes. The certain consultation papers take care of content material research for human-centered multimedia purposes; huge scale wealthy media information administration; multimedia knowing for buyer electronics; picture item acceptance and compression; and interactive photo and video search.
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Additional resources for Advances in Multimedia Modeling: 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part II
Recognizing human actions: a local svm approach. In: ICPR (2004) 13. : Simplest representation yet for gait recognition: averaged silhouette. In: ICPR (2004) 14. : Modelling crowd scenes for event detection. In: ICPR (2006) 15. : Hierarchical recognition of human activities interacting with objects. In: CVPR (2007) 16. : From videos to verbs: mining videos for activites using a cascade of dynamical system. In: CVPR (2007) 17. : Pair-activity classiﬁcation by bi-trajectory analysis. In: CVPR (2008) 18.
Taking the pairwise causality and feedback interactions as the example, we explored diﬀerent numbers of interaction patterns, varying from 8 to 256. The corresponding pLSA model was learnt against each number on the training sessions and then evaluated on the testing session. Fig. 5 shows the exploration results of the recognition performance against the variant amount of interaction patterns. From Fig. 5, we can observe some insight between the supposed pattern amount and the recognition performance.
Most of previous approaches ignored the selection of reference image, which is the basic frame for other sensed images in the process of registration. In our method, we introduce an effective evaluation for reference image selection. As the second development, a median-value image is utilized as the initialization in place of average image, the outperformance is demonstrated. Finally, we adopt a Weighted Cross Validation (WCV) to learn prior parameters. As we present, our is more efficient than the traditional Cross Validation.