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| Multi-sensor Fusion Based Vehicle Detection and Tracking Method |
| MAI Xin-Chen-a, YANG Ming-a, WANG Chun-Xiang-b, WANG Bing-a |
| (a. School of Electronic, Information and Electrical Engineering; b. School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China) |
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Abstract To fulfill real-time vehicle detection and track in city environment, a method based on laser radar and vision was presented. By perspective transform, vehicle hypothesis is done through laser radar. For vehicle recognition aspect, a method based on multi-dimension space Mahalanobis distance is presented, which extracts feature vector in ROI, and using the Mahalanobis distance between it and standard vector as presence probability. In vehicle tracking, the system uses Kalman filter to fulfill target tracking, at the mean time, to improve robustness, a particle-filter method based on Kalman filter is presented, it could realize more precise target state estimation when laser radar data does not work well. The experiment shows this method can achieve better vehicle tracking in general city environment.
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Received: 17 September 2010
Published: 29 July 2011
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