DocumentCode :
627013
Title :
Vehicle tracking iterative by Kalman-based constrained multiple-kernel and 3-D model-based localization
Author :
Kuan-Hui Lee ; Jenq-Neng Hwang ; Jen-Yu Yu ; Kual-Zheng Lee
Author_Institution :
Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA
fYear :
2013
fDate :
19-23 May 2013
Firstpage :
2396
Lastpage :
2399
Abstract :
In this paper, we propose a novel vehicle tracking system under a surveillance camera. The proposed system tracks vehicles by using constrained multiple-kernel facilitated with Kalman filtering, and then continuously updates the position and the orientation by adopting a systematically built 3-D vehicle model in an evolutionary computing framework. The proposed system can thus successfully track vehicles under occlusion as facilitated by the obtained 3-D geometry of vehicles. Experimental results have shown the favorable performance of the proposed system, which can successfully track vehicles while maintaining the knowledge of 3-D vehicle geometry.
Keywords :
Kalman filters; cameras; computational geometry; hidden feature removal; iterative methods; tracking; vehicles; video surveillance; 3D model-based localization; 3D vehicle geometry; Kalman filtering; Kalman-based constrained multiple-kernel; evolutionary computing framework; occlusion; surveillance camera; vehicle tracking system; Deformable models; Fitting; Image color analysis; Kernel; Shape; Solid modeling; Vehicles; modelbased visual localization; multiple kernels tracking; vehicle tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Conference_Location :
Beijing
ISSN :
0271-4302
Print_ISBN :
978-1-4673-5760-9
Type :
conf
DOI :
10.1109/ISCAS.2013.6572361
Filename :
6572361
Link To Document :
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