%0 Journal Article
%T Mean-Shift Object Tracking of Adaptive Tracking Window<br>自适应窗口选取的Mean-Shift目标跟踪
%A WANG Ming-jia
%A WU Zhi-guo
%A HAN Guang-liang
%A WANG Yan-jie
%A ZHANG Ye
%A <br>王明佳
%A 武治国
%A 韩广良
%A 王延杰
%A 张叶
%J 光子学报
%D 2012
%I 
%X To overcome the problem that traditional Mean-Shift based tracking method is easy to fail because of the rigid tracking window with the changing of object scales, a new algorithm to estimate the scale of the tracking window is proposed. It divides the template image and the current frame image into several concentric cirques. After calculating the comparability measurement of corresponding cirques between the template and the current image, it ascertains the bandwidth parameter of current frame. Finally, Kalman filter is adopt to finish the update of the template scale and the stable object tracking is realized. Experiments prove that the proposed algorithm is able to renew the template accurately when the scale of the object changes, and the tracking reliability is improved compared to the traditional Mean-Shift based tracking method.
%K Mean-Shift
%K Object tracking
%K Kernel baseband
%K Adaptive<br>Mean-Shift
%K 目标跟踪
%K 核函数带宽
%K 自适应性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=9F6139E34DAA109F9C104697BF49FC39&aid=1D36885FD7A8294BDC23E3C28A3947B9&yid=99E9153A83D4CB11&vid=2001E0D53B7B80EC&iid=CA4FD0336C81A37A&sid=5D71B28100102720&eid=4F2F18DD6F870C2C&journal_id=1004-4213&journal_name=光子学报&referenced_num=0&reference_num=14