摘要：

提出一种多姿态人脸特征定位方法，在Adaboost定位的人脸区域中划分眼、鼻和嘴的搜索区域，利用眉眼和鼻嘴整体特征，通过大规模多姿态五官样本训练的支持向量机在搜索区域中确定候选眼、鼻及嘴区域。对候选眼、鼻及嘴区域进行筛选与合并以确定最佳位置，实现多姿态人脸上五官的准确定位。实验结果表明，该方法具有较好的精确性和鲁棒性，能适应复杂背景下表情变化的多姿态人脸上的眼、鼻及嘴的定位。

关键词: 支持向量机, 人脸检测, 人脸特征定位, 眼睛检测, 多姿态眼睛定位

Abstract:

This paper proposes a method of multi-view face features localization. The face is located by AdaBoost detector and the search ranges of the face features are determined. The candidate eye, nose and mouth regions are found by the improved Support Vector Machine(SVM) detectors trained by large scale multi-view face features examples, which use the brow-eye and nose-mouth features. The candidate eye, nose and mouth regions are filtered and merged to refine their location on the multi-view face. Experimental results show that the method has very good accuracy and robustness to the face features localization with various face post and expression in the complex background.

Key words: Support Vector Machine(SVM), face detection, face features localization, eye detection, multi-view eye localization

中图分类号: 

• TP391