DocumentCode :
512789
Title :
A plane-geometry model for automatic detection of visual vehicle incident
Author :
Huang, Han ; Lu, Mengping ; Wang, Hongyang ; Ma, Xianheng ; Cai, Zhaoquan
Author_Institution :
Sch. of Software Eng., South China Univ. of Technol., Guangzhou, China
Volume :
1
fYear :
2009
fDate :
5-6 Dec. 2009
Firstpage :
350
Lastpage :
353
Abstract :
Automatic detection of vehicle incident by computer vision is one of the most important fields of video surveillance. In this paper, we propose a plane-geometry model to understand the vehicle behavior based on the visual information. The geometrical center of the vehicle-in-video object has different characters in different incidents. The vehicle objects of video are obtained by a background modeling approach, and their geometrical center is tracked by a meanshift-weight particle filter algorithm. The mathematic model of moving behavior of the tracked vehicle is for detecting the vehicle incidents including breaking, wrong-direction driving and wrong-lane driving. Finally, several traffic videos are tested, and the results indicate the proposed model is efficient, high-detection-rate and robust.
Keywords :
computer vision; traffic engineering computing; video surveillance; automatic detection; background modeling approach; breaking incident; computer vision; meanshift-weight particle filter algorithm; plane-geometry model; vehicle-in-video object; video surveillance; visual vehicle incident; wrong-direction driving incident; wrong-lane driving incident; Computer vision; Mathematical model; Mathematics; Particle filters; Particle tracking; Solid modeling; Vehicle detection; Vehicle driving; Vehicles; Video surveillance; Computer Vision; Image processing; activity understanding; automatic incident detection; vehicle tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Test and Measurement, 2009. ICTM '09. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4699-5
Type :
conf
DOI :
10.1109/ICTM.2009.5412919
Filename :
5412919
Link To Document :
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