Abstract: An improved multi-pose face detection algorithm based on facial features and AdaBoost algorithm was proposed. Making full use of facial skin color information firstly, most of the background regions could be quickly excluded. After detecting eyes and mouth, the approximate frontal face candidate regions were segmented according to face orientation decided by the geometric features of the eyes and mouth regions. At last, the face candidate regions were classified by AdaBoost algorithm. The experimental results demonstrate that the algorithm can further improve the multi-pose face detection accuracy and is highly robust to facial expression and occlusion.

Key words: face detection, multi-pose, skin color region, facial feature, AdaBoost algorithm, Harr-like feature

摘要： 基于人脸特征和AdaBoost算法，提出一种改进的多姿态人脸检测算法。首先利用肤色特征快速排除绝大部分背景区域，然后在肤色区域中搜索眼睛和嘴巴区域，根据眼睛和嘴巴区域的几何特征所确定的人脸方向分割出大致正向的人脸候选区域，最后利用AdaBoost算法对候选区域进行分类。实验表明，算法能实现多姿态人脸的快速检测，而且对脸部表情和遮挡有较强的鲁棒性。

关键词: 人脸检测, 多姿态, 肤色区域, 人脸特征, AdaBoost算法, Harr-like特征