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.
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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.
|Title:||A hierarchical framework for face tracking using state vector fusion for compressed video|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Computer Science|
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