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

Dorin Comaniciu, Visvanathan Ramesh and Peter Meer(*)

Imaging and Visualization Department
Siemens Corporate Research
Princeton, NJ 08540

(*)Department of Electrical and Computer Engineering
Rutgers University, Piscataway, NJ 08855, USA


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.

2000 Computer Vision and Pattern Recognition Conference , June 2000, Hilton Head Island, SC, vol.II, 142-149.
Return to Research: Robust analysis of visual data       Return to List of Publications
Download the paper