Abstract:

The background in the real life is relatively complex,and the effect of the Camshift target tracking based on the color feature are undesirable in complex situations.The modified Camshift based on spatial edge orientation histograms and optimized Kalman filters are adopted to predict the next possible position of the target in the video,and related OpenCV functions are used to reduce the failure of tracking.The position of search window is obtained by calculating the edge histogram and Kalman filter is used for forecast and feedback the information to determine next frame window position,which can overcome the occlusion and noise interference.Experiments show that the algorithm has good performance in the detection and tracking of the target.

Key words: video;edge orientation histogram;Camshift;Kalman;OpenCV;object tracking