We present a unique representation scheme for events in an area under surveillance, which provides a mechanism to analyze videos from multiple perspectives for unusual activity analysis. We propose clustering in event component spaces and define algebraic operations on these clusters to find co-occurrences of event components. A usualness measure for clusters is proposed that not only gives a measure on how usual or unusual an activity is, but also a basis for analyzing and predicting the possibly usual or unusual activities that can occur in the surveillance region. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Choudhary, A., Chaudhury, S., & Banerjee, S. (2007). Unusual activity analysis in video sequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4482 LNAI, pp. 443–450). Springer Verlag. https://doi.org/10.1007/978-3-540-72530-5_53
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