SRC最佳鉴别投影及其在人脸识别中的应用  

SRC optimal discriminant projection and its application in face recognition

作　　者：甘炎灵 金聪[1] 

机构地区：[1]华中师范大学计算机学院,湖北武汉430079

出　　处：《计算机工程与科学》2016年第11期2282-2288,共7页Computer Engineering & Science

基　　金：国家社会科学基金(13BTQ050)

摘　　要：根据稀疏表示分类器的分类准则,提出了一种稀疏表示分类器最佳判别的投影方法。该方法优化两个目标,一是数据集的类间和类内稀疏重构误差,二是数据集中区分度。优化结果使样本投影到低维空间中,确保SRC具有更好的分类性能。在AR和Yale数据库上进行人脸识别实验,并与几种流行的方法进行了比较,结果表明所提出的方法具有良好的有效性和鲁棒性。We propose a SRC optimal discriminant projection method according to the classification criteria of the sparse representation classifier （SRC）. There are two optimized goals： one is the sparse reconstruction residual betweenclass and withinclass of the data set, the other is the distinction of samples in the data set, which can achieve a higher classification accuracy of the SRC when the samples are projected into a low dimension space. Face recognition experiments conducted on the AR and Yale databases show that the proposed method is more effective and robust in comparison with several other popular methods.

关 键 词：稀疏表示分类器 判别投影 人脸识别 分类性能 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]