Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real Time Face and Object Tracking as a Component of a Perceptual User Interface
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
In this paper, we discuss methods to enable robust surveillance on compressed video. We show that if the particular surveillance algorithm that is likely to be run on the compressed video is known apriori, then steps can be taken during the encoding process to facilitate the performance of the algorithm. We show that by performing signal processing on the input video signal before it is encoded, or by adaptively changing the parameters of the encoding process, we can make the resulting signal more robust to degradations in the encoding process. The result is better and more consistent tracking on the compressed video from high to low bitrates, but with some loss in PSNR. We demonstrate the validity of this approach for Mean Shift tracking running on MPEG-4 coded video.