Enhanced Face Detection and Tracking In Video Sequence Using Fuzzy Face Model and Sparse Representation Technique

Abstract The human face detection from video sequences is an important biometric component in the design of intelligent human computer interaction systems for video surveillance, face recognition, emotion recognition and face database management. In this paper, an automatic and robust method to detect human faces from video sequences and track the same is proposed. A novel algorithm for segmentation of face regions in video images based on fuzzy geometric face model is developed. The sparse representation algorithm is used to track the face along the video sequence. The proposed method, which is developed as a simple face detection and tracking approach, is implemented and evaluated with numerous experiments on videos containing large variations of head motion, light condition, and facial expressions. The experimental results show that the proposed method is effective in detecting and tracking human faces in videos.