计算机技术与发展2018，Vol.28Issue(2)：59-63,5.DOI:10.3969/j.issn.1673-629X.2018.02.014
基于稀疏表示和支持向量机的人脸识别算法
A Face Recognition Algorithm Based on Sparse Representation and Support Vector Machine
摘要
Abstract
With the development and application of face recognition technique,the face recognition methods are also diversified at present. The face recognition method based on sparse representation classification(SRC) is a global linear method based on the rise of compression perception theory.Based on the previous research,we propose solving the sparse representation model by orthogonal matching pursuit (OMP) instead of gradient projection for sparse reconstruction (GPSR).The sparse threshold is set to control the sparsity of sparse coeffi-cients,eliminating the phenomenon that nonzero coefficients appear in nonclass samples.In addition,the recognition criterion of face recogni-tion based on SRC is the minimum reconstruction residuals.For a test sample,it is necessary to calculate its similarity to each other one and the recognition efficiency is low.For this shortcoming,we propose a multi-class support vector machine as the final classification tool.The results on ORL show that this method can improve the speed and accuracy of face recognition.关键词
人脸识别/稀疏表示/正交匹配追踪法/多分类支持向量机Key words
face recognition/sparse representation/orthogonal matching pursuit/multi-class SVM分类
信息技术与安全科学引用本文复制引用
徐静妹,李雷..基于稀疏表示和支持向量机的人脸识别算法[J].计算机技术与发展,2018,28(2):59-63,5.基金项目
国家自然科学基金(61070234,61071167,61373137) （61070234,61071167,61373137）
