A Sensor fusion based object tracker for compressed video
Radhakrishna Achanta, Wang, J, Kankanhalli · UCL Discovery (University College London) · 2003
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. KeywordsMPEG compressed domain; Kalman filtering; sensor fusion