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A SVM face recognition method based on Gabor-featured key points

机译:基于Gabor特征关键点的SVM人脸识别方法

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This paper presents a novel face recognition approach based on support vector machine and Gabor-featured key points, which takes technological advantages of both support vector machine and Gabor feature extraction. The main contributions of this paper therefore lie in the following aspects: (1) support vector machine is successfully applied to face recognition by using Gabor features of key points; (2) Gabor features of key points are introduced to represent a whole face in a computable dimensional space. As a result, experiments on FERET and AT&T databases have shown significant better performance with this method, which in itself proves the feasibility of our proposal.
机译:本文提出了一种基于支持向量机和Gabor特征关键点的人脸识别新方法,它利用了支持向量机和Gabor特征提取的技术优势。因此,本文的主要贡献在于以下几个方面:(1)利用关键点的Gabor特征成功地将支持向量机应用于人脸识别。 (2)引入关键点的Gabor特征,以表示可计算维空间中的整个面孔。结果,在FERET和AT&T数据库上进行的实验表明该方法具有明显更好的性能,这本身就证明了我们建议的可行性。

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