Abstract: Aiming at the problem that the tracking ability decreases due to occlusion during the tracking of video human moving objects, an adaptive tracking algorithm for video human moving objects considering the occlusion factor is proposed. The Kalman filter and the Meanshift tracking algorithm are used to track the video human moving target. When the target scale, rotation and light change there poor tracking results. The SIFT( Scale Invariant Feature Transform) algorithm is introduced to improve the tracking ability and achieve anti-occlusion video human moving target adaptive tracking. The experimental results show that the tracking accuracy of this method is high, and the tracking success rate can reach about 75% when the occlusion degree is 0. 5. The average tracking frame rate is 28. 9 frame / s, and the real-time performance is strong.

Key words: occlusion factor,  , human motion target,  , kalman filter,  , target tracking,  , scale invariant feature transform(SIFT) algorithm