基于线性组合模型的人脸特征检测方法

A Facial Feature Extraction Method Based on Linear Combination Model

为了实现人脸图像特征的自动检测,提出了一种基于线性组合模型的人脸特征检测新方法.该方法通过原型人脸标定获取人脸特征知识,并使用模型匹配来检测目标人脸特征.在建立人脸线性组合模型的过程中,提出了局部约束光流算法,解决了有局部特征信息的人脸图像稠密对应问题.在MPI和ORL人脸数据库上进行的人脸特征检测得到的平均误差分别为96.7%和86%,该结果表明了基于线性组合模型的人脸特征检测方法是有效和实用的.

Based on linear combination model, a new facial feature extraction method is proposed. By matching procedure, the combination model extracts automatically the feature points of given facial image from the information of the labeled prototypes. To construct linear combination model, a restrained optical flow algorithm is proposed to solve the difficult problem of the pixel-wise alignments among the labeled prototypic faces. By implementing the feature extraction method on the MPI and ORL face database, we gain average error 96.7 % and 86 % respectively. The result shows that the method has good performance.