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Video Content Classification
In: http://www.ismll.uni-hildesheim.de/lehre/semML-09s/script/p183-fleischman.pdf
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Video Content Classification
In: http://web.media.mit.edu/~dkroy/papers/pdf/fleischman_decamp_2006.pdf
Abstract: Scalable approaches to video content classification are limited by an inability to automatically generate representations of events that encode abstract temporal structure. This paper presents a method in which temporal information is captured by representing events using a lexicon of hierarchical patterns of movement that are mined from large corpora of unannotated video data. These patterns are then used as features for a discriminative model of event classification that exploits tree kernels in a Support Vector Machine. Evaluations show the method learns informative patterns on a 1450-hour video corpus of natural human activities recorded in the home.
Keyword: Experimentation. Keywords Temporal Data Mining; General Terms Algorithms; Support Vector Machine; Tree Kernel; Video Content Classification; Video Event Recognition
URL: http://web.media.mit.edu/~dkroy/papers/pdf/fleischman_decamp_2006.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.151.1602
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