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Real-time vehicles tracking based on Kalman filter in a video-based ITS

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5 Author(s)
Lei Xie ; Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., China ; Guangxi Zhu ; Yuqi Wang ; Haixiang Xu
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Tracking vehicles is an important and challenging issue in video-based intelligent transportation systems and has been broadly investigated in the past. This paper presents a robust and real-time method for tracking vehicles and the proposed algorithm includes two stages: vehicle detection, vehicle tracking. Vehicle detection is a key step and the concept of tracking vehicle is built upon the vehicle-segmentation method. According to the segmented vehicle shape, we propose a three-step prediction method based on the Kalman filter to track each vehicle. The proposed method has been tested on a number of monocular traffic-image sequences and the experimental results show that the algorithm is robust and real-time. The correct rate of vehicle tracking is higher than 85 percent, independent of environmental conditions.

Published in:

Proceedings. 2005 International Conference on Communications, Circuits and Systems, 2005.  (Volume:2 )

Date of Conference:

27-30 May 2005