A Fast Video Frame Segmentation Scheme
Background subtraction is a technique for detecting moving objects in video frames. A simple BS process involves building a model of the background and extracting regions of the foreground (moving objects) with the assumptions that the camera remains stationary and there exist no movements in the background. Video object extraction is a critical task in multimedia analysis and editing. Normally, the user provides some hints of foreground and background, and then the target object is extracted from the video sequence. In this paper, we propose a object segmentation system that integrates a clustering model with Markov random field-based contour tracking and graph-cut image segmentation. The contour tracking propagates the shape of the target object, whereas the graph-cut refines the shape and improves the accuracy of video segmentation. Experimental results show that our segmentation system is efficient.
clustering model Video object extraction Markov random filed graph-cut
Shilin Zhang
Faculty of Computer Science Network and Information Management Center Beijing, China
国际会议
上海
英文
179-182
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）