基于肤色模型与人脸特征的多姿态人脸检测

传统AdaBoost人脸检测算法使用正面人脸训练分类器,不能检测有任意偏转角度的多姿态人脸。本研究利用各种多姿态人脸中人眼结构变化比较小的性质,使用人眼训练AdaBoost算法的分类器,设计出一种快速的复杂场景下的多人多姿态人脸检测算法。先将图像映射到一种色彩空间,运用皮肤颜色分布特性检测皮肤区域;再运用AdaBoost算法从肤色区域检测出人眼区域;最后根据人眼在人脸中的位置计算出人脸的位置。实验结果表明:该算法对多姿态人脸有很好的检测效果。

Multi-pose face detection based on color model and face feature

Traditionally,AdaBoost based face detection algorithms use frontal faces to train classifiers,which cannot detect multi-pose faces with arbitrary rotations.Noticing that the eye structures vary less than face structures in multi-pose faces,eyes were used to train the classifier in AdaBoost algorithm,and present a fast algorithm to detect multi-pose faces in complex scenes.An image is first mapped to a YCrCb color space and the skin region is detected with the skin color distribution.The eye region is then d...