Aiming at fulfilling the wide-area video surveillance, this paper presents a cooperative multi-camera target tracking method for wireless camera sensor networks. In the proposed method, target detection is carried out by single-node processing based on background subtraction, whereas target tracking is performed by senor nodes cooperation based on automatic node selection. The main contributions of the proposed method are summarized as follows. First, each camera node uses an adaptive Gaussian mixture model to extract moving targets and an unscented Kalman filter to solve target tracking. Second, the correspondence between the targets in different camera views is established by homography transformation of target positions. Third, a confidence measure based on the size of the detected target blob and the estimate uncertainty of tracking is defined to achieve optimal node selection. Experimental results show that the proposed method can effectively select camera node to implement the accurate tracking in real scenes.
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