计算机工程Issue(11)：160-166,7.DOI:10.3969/j.issn.1000-3428.2014.11.032
泛化改进的局部切空间排列算法
Local Tangent Space Alignment Algorithm of Generalized Improvement
摘要
Abstract
The Improved Local Tangent Space Alignment ( ILTSA ) can obtain better low dimension feature for face recognition because it can efficiently recover the problem that the Local Tangent Space Alignment( LISA) fails to reveal the manifold structure in the case when data are sparse or non-uniformly distribute or when the data manifold has large curvatures. To solve the problem that the ILTSA cannot efficiently handle ever-increasing data set,this paper presents a Generalization method for the ILTSA( GILTSA) . The nearest neighborhood set is obtained based on the distance defined according to the classes of the samples, then the low manifold of the training set is implemented using the ILTSA. Through finding the nearest sample in the training set,and the low manifold of a new sample is approximately calculated by the projection of its nearest sample. Experimental results on the ORL,the Yale and the University of Essex face image database indicate that the proposed GILTSA method increases the overall accuracy compared with Principal Component Analysis( PCA) and Linear Local Tangent Space Alignment( LLTSA) algorithm etc.关键词
流形学习/局部切空间排列/泛化/特征提取/人脸识别Key words
manifold learning/Local Tangent Space Alignment(LTSA)/generalization/feature extraction/face recognition分类
信息技术与安全科学引用本文复制引用
赵辽英,李富杰,厉小润..泛化改进的局部切空间排列算法[J].计算机工程,2014,(11):160-166,7.基金项目
国家自然科学基金资助项目(61171152) （61171152）
浙江省自然科学基金资助项目(LY13F020044)。 （LY13F020044）
