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Conference Papers Year : 2009

Crowd Event Recognition using HOG Tracker


The recognition in real time of crowd dynamics in public places are becoming essential to avoid crowd related disasters and ensure safety of people. We present in this paper a new approach for Crowd Event Recognition. Our study begins with a novel tracking method, based on HOG descriptors, to finally use pre-defined models (i.e. crowd scenarios) to recognize crowd events. We define these scenarios using statistics analysis from the data sets used in the experimentation. The approach is characterized by combining a local analysis with a global analysis for crowd behavior recognition. The local analysis is enabled by a robust tracking method, and global analysis is done by a scenario modeling stage.
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Dates and versions

inria-00515197 , version 1 (06-09-2010)
inria-00515197 , version 2 (14-12-2012)



Carolina Garate, Piotr Bilinski, François Bremond. Crowd Event Recognition using HOG Tracker. Twelfth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS-Winter), Dec 2009, Snowbird, UT, United States. pp.1-6, ⟨10.1109/PETS-WINTER.2009.5399727⟩. ⟨inria-00515197v2⟩


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