DocumentCode :
2498822
Title :
Crowd behavior analysis under cameras network fusion using probabilistic methods
Author :
Drews, Paul ; Quintas, J. ; Dias, J. ; Andersson, M. ; Nygårds, J. ; Rydell, J.
Author_Institution :
Inst. of Syst. & Robot., Univ. of Coimbra, Coimbra, Portugal
fYear :
2010
fDate :
26-29 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
The use of cameras in surveillance is increasing in the last years due to the low cost of the sensor and the requirement by surveillance in public places. However, the manual analysis of this data is impracticable. Thus, automatic and robust methods to processing this high quantity of data are required. This paper proposes a framework to address this problem. The crowd analysis is achieved in camera networks information by using the optical flow. The Hidden Markov models and Bayesian Networks are compared to understand the agents behavior in the scene. The experimental results are obtained for several sequences where fight and robbery occurs. Results are promise in order to get an automatic system to find abnormal events.
Keywords :
Markov processes; behavioural sciences computing; belief networks; image sequences; multi-agent systems; probability; sensor fusion; video cameras; video surveillance; Bayesian networks; agents behavior; automatic system; camera networks information; cameras network fusion; crowd behavior analysis; hidden Markov models; optical flow; probabilistic methods; public places; surveillance camera; Asynchronous transfer mode; Bayesian methods; Cameras; Hidden Markov models; Legged locomotion; Mathematical model; Optical sensors; Bayesian Networks; Behavior Analysis; Hidden Markov Models; Sensor Fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2010 13th Conference on
Conference_Location :
Edinburgh
Print_ISBN :
978-0-9824438-1-1
Type :
conf
DOI :
10.1109/ICIF.2010.5712106
Filename :
5712106
Link To Document :
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