Real time head region tracking system based edge restoration using the K-means method

This paper presents a fast frontal face detection method. We use motion segmentation algorithm that makes use of differencing to detect moving people’s faces. The novelty of this paper comes from the differencing in real time input images, preprocessing to remove noises (morphological operator and so on), detecting edge lines and restoration, finding the face area and cutting the head candidate. Moreover, we adopt K-means algorithm for finding head. Our system applies the statistical modeling of face and non – face classes to verify and classifies multiple frontal face images with the Bayesian Discriminating Features (BDF) method. Finally experimental results (using capture diverse image sources for 13 frames per second during 20 seconds and having 260 images per person) shows the feasibility of the differencing Based Head and Face Detection method.