Face segmentation in head-and-shoulder video sequences based on facial saliency map
In this paper, a novel face segmentation algorithm is proposed based on facial saliency map (FSM) for head-and-shoulder type video application. This method consists of three stages. The first stage is to generate the saliency map of input video image by our proposed facial attention model. In the second stage, a geometric model and a eye-map built from chrominance components are employed to localize face region according to the saliency map. The third stage involves the adaptive boundary correction and the final face contour extraction. Experimental evaluation on test sequences shows that the proposed method is capable of segmenting and tracking the face area quite effectively