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
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