Automatic foreground extraction for images and videos
Zhen Tang, Zhenjiang Miao, Yanli Wan, Jia Li · 2010
In this paper, an automatic foreground extraction algorithm for images and videos is presented. It first automatically locates the foreground object coarsely by a salience detection algorithm, and then refines the object by Weighted Kernel Density Estimation (WKDE) and graph cut algorithm. A new initial probability map construction algorithm for WKDE is also presented. We then extend our algorithm to videos by an opacity tracking algorithm. It can automatically extract the foreground with high accuracy even for the videos with non-static background. The experiments demonstrate the effectiveness of our approach.