A multi-target tracking algorithm using texture for real-time surveillance

Authors:
Zhixu Zhao;Shiqi Yu;Xinyu Wu;Congling Wang;Yangsheng Xu
Affiliations:
Center for Intelligent and Biomimetic Systems, Shenzhen Institute of Advanced Technology, CAS, China;Center for Intelligent and Biomimetic Systems, Shenzhen Institute of Advanced Technology, CAS, China;Center for Intelligent and Biomimetic Systems, Shenzhen Institute of Advanced Technology, CAS, China;School of Mechatronics Engineering, University of Electronics Science and Technology of China, Chengdu, China;Center for Intelligent and Biomimetic Systems, Shenzhen Institute of Advanced Technology, CAS, China
Venue:
ROBIO '09 Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics
Year:
2009

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Abstract

In this paper, we present a texture-based multitarget tracking algorithm. Moving objects are described by local binary patterns (LBP), which is a kind of discriminative texture descriptor. The Kalman filter is introduced into the algorithm to predict the blob's new position and size. Blobs are searched in the neighborhood of the Kalman predictions. If more than one are found, the LBP distance, which has been evaluated valid for blob distinguishing in our experiments, is applied to locate the tracking target. Cooperates with the LBP distance, the Kalman filter is efficient in dealing with collisions. Tracking results demonstrate the effectiveness of the algorithm. This algorithm has been implemented on PC and DSP platforms and achieved real-time performance.