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

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 nds 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 coe cient. The theoretical analysis of the approach shows that it relates to the Bayesian framework while providing a practical, fast and e cient solution. The capability of the tracker to handle in real-time partial occlusions, signi cant clutter, and target scale variations, is demonstrated for several image sequences.

• Type: Conference
• Year: 2000
• Where: CVPR
• Authors: Dorin Comaniciu, Visvanathan Ramesh, Peter Meer
• Keywords: Computer Vision, CVPR 2000, Probable Target Position, Real-time Partial Occlusions, Target Candidates, Target Model, Target Scale Variations