A Sensor fusion based object tracker for compressed video

Object tracking is very important for automatic indexing of video content. This work shows tracking of objects directly using compressed MPEG video data. Two sensors, one using motion vectors and the other using DCT coefficients obtained from compressed video stream, provide measurements for the location of the object being tracked. The optimal estimate from the two measurements is found using Kalman filtering based state vector fusion approach. Keywords—MPEG compressed domain; Kalman filtering; sensor fusion

[1]  Mohan S. Kankanhalli,et al.  Compressed domain object tracking for automatic indexing of objects in MPEG home video , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[2]  Yiqiang Zhan,et al.  Rapid Object Tracking on Compressed Video , 2001, IEEE Pacific Rim Conference on Multimedia.

[3]  Wen-Nung Lie,et al.  Tracking moving objects in MPEG-compressed videos , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[4]  Lorenzo Favalli,et al.  Object tracking and hypermedia links creation in MPEG-2 digital video sequences , 1998, ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187).