关键词: 人脸识别, 单训练样本, trace变换, 特征提取, 特征匹配

Abstract: A face recognition algorithm based on invariant feature of trace transform is presented to improve the recognition rate of single training sample in variations of pose and expression. With application of one order Scharr operator and second order scale-adapted Laplacian of Gaussian （LoG） & Harris filter, feature points are detected. Proper functionals are chosen to perform trace transform in the circular region around each feature point so as to achieve feature descriptors which are invariant to rotation and scaling. A coarse-to-fine matching strategy is conducted by applying the descriptor’s feature vectors and coordinates. It guarantees the stability as no problem of parameter selection. The experimental results demonstrate that this method decreases the effect caused by the variations of pose and expression and also reduces the running time.

Key words: face recognition, single training samples, trace transform, feature extraction, feature matching