Description

Automatic Face Segmentation for Real-Time Video

In this project, face recognition and verification is most important factor in security system.Segmenting human faces automatically is very important factor in security system.We present an accurate segmentation system for cutting human faces out from video sequences in real-time. First, a learning based face detector is developed to rapidly find human faces. To speed up the detection process, a face rejection cascade is constructed to remove most of negative samples while retaining all the face samples. Then, we develop a coarse-to-fine segmentation approach to extract the faces based on a min-cut optimization. Finally, a new matting algorithm is proposed to estimate the alpha-matte based on an adaptive trimap generation method. Experimental results demonstrate the effectiveness and robustness of our proposed method that can compete with the well-known interactive methods in real-time.