Real-Time Tracking of Non-Rigid Objects Using Mean Shift

D Comaniciu,V Ramesh,P Meer

Computer Vision and Pattern Recognition (CVPR)（2000）CCF A

Siemens Corp Res

被引用4919|浏览1110

摘要

A new method for real time tracking of non-rigid objects seen from a moving camera is proposed. The central computational module is based on the mean shift iterations and finds the most probable target position in the current frame. The dissimilarity between the target model (its color distribution) and the target candidates is expressed by a metric derived from the Bhattacharyya coefficient. The theoretical analysis of the approach shows that it relates to the Bayesian framework while providing a practical, fast and efficient solution. The capability of the tracker to handle in real time partial occlusions, significant clutter, and target scale variations, is demonstrated for several image sequences

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关键词

Bayes methods,computer vision,image sequences,iterative methods,optical tracking,real-time systems,Bayesian framework,Bhattacharyya coefficient,clutter,color distribution,computational module,image sequences,mean shift iterations,most probable target position,moving camera,non-rigid object tracking,partial occlusions,real time tracking,target candidate,target model,target scale variations