Towards facial feature extraction and verification for omni-face detection in video/images

Face detection is important in video/image content analysis and organization since the most important object in those media is often a human being. We propose a facial feature based omni-face detection algorithm. While utilizing the skin color model for face cue detection, a pairwise skin region refinement strategy is applied to eliminate the errors incurred by the skin model. Then, a region based adaptive threshold selection scheme is employed for facial feature segmentation. After the facial feature filtering, an orientation, pose and scale invariant face verification strategy is utilized to verify the detected face candidate regions. Experimental results demonstrate successful detection over a wide variety of facial variation in background, scale, view and orientation from different types of video collections.