基于尺度不变特征变换和支持向量机的人脸识别

Lichun Zhang, Junwei Chen, Yue Lu, P. Wang
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引用次数: 36

摘要

在过去的几十年里,人脸识别在许多潜在的应用中受到了极大的关注。近年来,尺度不变特征变换(SIFT)成为目标识别的一种重要技术。研究了SIFT方法在人脸识别中的应用,提出了一种基于SIFT和支持向量机的人脸识别新方法。首先生成SIFT特征,然后使用SVM进行分类。在ORL数据库和Yale人脸数据库中进行了测试,结果表明该方法在不同表情条件下具有良好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face Recognition Using Scale Invariant Feature Transform and Support Vector Machine
Face recognition has received significant attention in the last decades for many potential applications. Recently, the scale invariant feature transform (SIFT) becomes an interesting technique for the task of object recognition. This paper investigated the application of the SIFT approach to the face recognition and proposed a new method based on SIFT and support vector machine (SVM) for the face recognition problem. First the SIFT features are generated and then SVM is used for the classification. The presented method has been tested with the ORL database and the Yale face database, and the recognition results demonstrate its robust performance under different expression conditions.
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