Mean-shift background image modelling
- Publication Type:
- Conference Proceeding
- Proceedings - International Conference on Image Processing, ICIP, 2004, 2 pp. 3399 - 3402
- Issue Date:
Background modelling is widely used in computer vision for the detection of foreground objects in a frame sequence. The more accurate the background model, the more correct is the detection of the foreground objects. In this paper, we present an approach to background modelling based on a mean-shift procedure. The mean shift vector convergence properties enable the system to achieve reliable background modelling. In addition, histogram-based computation and the new concept of local basins of attraction allow us to meet the stringent real-time requirements of video processing. ©2004 IEEE.
Please use this identifier to cite or link to this item: