An automated system for crowd behaviour analysis has gained significance in the context of surveillance and public management. Detecting the changes in the crowd behaviour demarcates one activity or event from another. Thus, change detection is a fundamental step that enables the subsequent characterisation of the activities and analysis of the transition from one state to another. Proposed work deals with high density crowd. Global motion is an important cue for studying the behaviour of such crowd. In this work, crowd motion is modelled using beta distribution. Change in the distribution parameter is an indicator for change in crowd motion pattern. Proposed methodology has been tested with number of synthetic and natural video sequences and the performance is satisfactory.
CITATION STYLE
Pal, S., Mondal, S., Saha, S. K., & Chanda, B. (2016). A beta distribution based novel scheme for detection of changes in crowd motion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10481 LNCS, pp. 192–203). Springer Verlag. https://doi.org/10.1007/978-3-319-68124-5_17
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