关键词: 局部保持投影（LPP）, 回归森林, 人脸特征点, 全局特征, 头部姿态

Abstract: Due to changes in the reality are linear physics position changes while in the image space are nonlinear, thus head pose has great influence for facial feature detection. In this paper, it proposes a precision head pose estimation method as a condition of regression forests, the algorithm modifies the performance of the nonlinear problem into a linear one. The main idea is used by Locality Preserving Projection and Nonlinear Regression（LPP+NLR） for obtaining the global information of pose and label, then, it utilizes trained conditional regression classifier to identify the feature points in global characteristics. Experimental results show that the algorithm decreases the missing rate caused by head deflection, and increases the precision of facial feature point detection.

Key words: Locality Preserving Projection（LPP）, regression forests, facial feature detection, global feature, head pose