Flow-Process Foreground Region of Interest Detection Method for Video Codecs

Detecting the foreground region of interest (ROI) for video sequences is an important issue both for video codecs and monitoring systems. In this paper, we propose a flow-process-based method to detect foreground ROI using four steps: global motion compensation, motion block extraction, multi-layer segmentation, and model updating. The former two procedures extract the foreground motion blocks and form a motion mask, and the latter two procedures remove the pixels belonging to the background inside the motion mask and update the color distributions of the background model. In addition, a block-based to pixel-based detection scheme is proposed to allow detection flexibility. Another benefit of the proposed method is that it can be embedded in video codecs for real-time ROI detection and encoding. Experimental results demonstrate that our method achieves improved performance in terms of both detection accuracy and time consumption.