关键词: Mean Shift, 卡尔曼滤波器, 目标跟踪, 遮挡检测

Abstract: We employ Kalman filter to choose the start point for Mean Shift tracking algorithm and update the target model to avoid the accumulative error result from the tardy change of target.Kalman filter error is exploited to decide whether the occlusion detection algorithm works,which divides the target into four parts and detects respectively.And occlusion is classified into two categories： partial occlusion and complete occlusion,we utilize the velocity of the target to present six-point research strategy to deal with complete occlusion.Experimental results show that the algorithm is robust to solve occlusion problem.

Key words: Mean Shift, Kalman filter, object tracking, occlusion detection