Real-time face and head detection using four directional features

Real-time human detection is an important part in a surveillance system using computer vision. In this paper, a real-time face and head detection method is proposed for such human detection. The method has an advantage of detecting peoples who are not facing a camera, by detecting their heads. It employs four directional features (FDF) and linear discriminant analysis in order to save computation cost for scanning and classification. Since FDF represents edge directional information in low resolution, it is resistive to changes in lighting conditions and scales. The proposed method was evaluated through an experiment using 26 video scenes. The results of experiment were 83.6% (46/55) for human detection rate, and 84.6% (1048/1239) for reliability of detection. The human detection system implemented with the proposed method runs on a PC at approximately over 10 fps for VGA input with motion detection.