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小样本条件下采用Gabor特征的人脸识别
Face Recognition Using Gabor Feature with Small Samples
【摘要】 人脸表征和特征提取是人脸识别中的关键问题 针对Gabor特征的识别能力问题 ,利用点分布模型和类别可分离性判据研究了人脸不同位置和不同Gabor展开系数的分类能力 实验结果表明 ,合理地构造Gabor特征和选择特征点位置 ,能够提高识别率和减少特征数量 在此基础上 ,提出了在小样本条件下结合主动形状模型和Gabor特征进行人脸识别的方法
【Abstract】 Face representation and feature extraction are the key problems to face recognition. We perform feature selection based on PDM and discriminating power of Gabor features in different locations, orientations and scales. Experiments show that these methods achieve higher recognition rate with fewer features. In the paper we have also proposed a novel face recognition method based on active shape model (ASM) and Gabor transform.
【关键词】 人脸识别;
Gabor变换;
点分布模型;
主动形状模型;
【Key words】 face recognition; Gabor transform; point distribution model; active shape model;
【Key words】 face recognition; Gabor transform; point distribution model; active shape model;
- 【文献出处】 计算机辅助设计与图形学学报 ,Journal of Computer Aided Design & Computer Graphics , 编辑部邮箱 ,2005年02期
- 【分类号】TP391.4
- 【被引频次】25
- 【下载频次】453