Face Detection Based on Facial Features and Linear Support Vector Machines
Jinxin Ruan, Junxun Yin · 2009
Face detection is a complicated and significant problem in pattern recognition and has wide application. This paper proposes a fast face detection algorithm based on facial features and linear Support Vector Machines (LSVM). First, using of skin color information, the algorithm quickly excludes most background regions from the images primarily leaving the skin color regions. Then we use LSVM to separate more non-face regions from the remaining regions, for exiting big differences between the face regions and non-face regions. Finally, we identify the face candidates by detecting eyes and mouth. The experimental results demonstrate that the algorithm can further improve the detection accuracy and lower false detection rate and greatly speed up the detection rate.