For many computer vision problems, it is very important to produce the groundtruth data. Manual data labeling is labor-intensive and prone to the human errors, whereas fully autom...
Facial feature tracking is a crucial and challenging task in computer vision. Recently online-learning methods have become increasingly popular on account of their strong ability ...
Foreground segmentation is one of the most challenging problems in computer vision. In this paper, we propose a new algorithm for static camera foreground segmentation. It combine...
A split-and-merge framework based on a maximum variance criterion is proposed for disparity clustering. The proposed algorithm transforms low-level stereo disparity information to...
Image attention is the basic technique for many computer vision applications. In this paper, we propose an adaptive Bayesian framework to detect the image attention in color image...