DocumentCode :
3016680
Title :
Integrating pedestrian simulation, tracking and event detection for crowd analysis
Author :
Butenuth, Matthias ; Burkert, Florian ; Schmidt, Florian ; Hinz, Stefan ; Hartmann, Dirk ; Kneidl, Angelika ; Borrmann, André ; Sirmacek, Beril
Author_Institution :
Remote Sensing Technol., Tech. Univ. Munchen, Munich, Germany
fYear :
2011
fDate :
6-13 Nov. 2011
Firstpage :
150
Lastpage :
157
Abstract :
In this paper, an overall framework for crowd analysis is presented. Detection and tracking of pedestrians as well as detection of dense crowds is performed on image sequences to improve simulation models of pedestrian flows. Additionally, graph-based event detection is performed by using Hidden Markov Models on pedestrian trajectories utilizing knowledge from simulations. Experimental results show the benefit of our integrated framework using simulation and real-world data for crowd analysis.
Keywords :
Markov processes; graph theory; image sequences; object tracking; pedestrians; traffic engineering computing; Markov models; crowd analysis; dense crowds; graph based event detection; image sequences; pedestrian flows; pedestrian simulation; pedestrian tracking; Data models; Event detection; Feature extraction; Hidden Markov models; Image color analysis; Kernel; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4673-0062-9
Type :
conf
DOI :
10.1109/ICCVW.2011.6130237
Filename :
6130237
Link To Document :
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