UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

A hierarchical framework for face tracking using state vector fusion for compressed video

Wang, J; Achanta, R; Kankanhalli, MS; Mulhem, P; (2003) A hierarchical framework for face tracking using state vector fusion for compressed video. In: 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings. (pp. 209 - 212). IEEE Computer Society: Piscataway, US.

Full text not available from this repository.

Abstract

Faces usually are the most interesting objects in certain categories of video, like home videos and news clips. A novel sensor fusion based face tracking system is presented that tracks faces in compressed video, and aids automatic video indexing. Tracking is done by fusing the measurements from three independent sensors - motion and colour based trackers (Achanta, R. et al., IEEE Int. Conf. on Multimedia and Expo, 2002) and a face detector (Wang, J. et al., Proc. Int. Workshop on Advanced Image Technology, 2002) using a novel hierarchical framework based on Kalman filter state vector fusion. The tracking results show that the fused results are better than those of any individual sensors or their mean.

Type:Proceedings paper
Title:A hierarchical framework for face tracking using state vector fusion for compressed video
ISBN:0780376633
DOI:10.1109/ICASSP.2003.1199144
Publisher version:http://dx.doi.org/10.1109/ICASSP.2003.1199144
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

Archive Staff Only: edit this record