Robust objects tracking algorithm based on adaptive background updating
For solving the problem of false tracking by Continuously Adaptive Mean Shift (CAMSHIFT) algorithm when sharing significant color similarity between object and background and changes of object color, moreover, for avoiding selecting initial target object by hand, an adaptive robust objects tracking algorithm based on active camera is proposed. It uses the disparity of global and local motion to detect the motion area. Then, it segments each object by an improved K-Mean clustering algorithm. Finally, it tracks the object by the improved adaptive background updating CAMSHIFT algorithm continuously in real time. The effectiveness of this proposed algorithm has been proved by preceding experiments on real time video sources. Compared to the state of the art methods, the algorithm in this paper is more robust and effective.
Active camera speed discrepancy K-Mean CAMSHIFT
Yi Wei Zhao Long
Science and Technology on Aircraft Control Laboratory, Beihang University Digital Navigation Center, Beihang University Beijing 100191, China
国际会议
IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)
北京
英文
190-195
2012-07-25（万方平台首次上网日期，不代表论文的发表时间）