关键词: 目标跟踪, 非线性核密度估计, CAMShift, Kalman滤波, 直方图, 遮挡处理

Abstract: For the problem of Mean Shift algorithm extracting the target color features easily affected by the background, this paper selects non-linear kernel density estimation to detect single moving object, then uses CAMShift method to track the detected target, combined with test results of nonlinear kernel density estimation to do adaptive update of target histogram. This article also gives solution of target occlusion problem. Experimental results show that the method which combines the foreground detection and CAMShift can achieve automatic tracking of moving target, as well as adaptive update of target histogram. The reliable performance of this algorithm can satisfy real-time requirement, and eliminate the effects of unstable scene illumination and object occlusion.

Key words: target tracking, non-linear kernel density estimation, CAMShift, Kalman filter, histogram, occlusion handling