DocumentCode
2497318
Title
Orthogonal linear local spline discriminant embedding for face recognition
Author
Lei, Ying-Ke ; Hu, Rong-Xiang ; Tang, Lei ; Zhang, Shan-Wen ; Huang, De-Shuang
Author_Institution
Intell. Comput. Lab., Chinese Acad. of Sci., Hefei, China
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
8
Abstract
In this paper, an efficient feature extraction algorithm called orthogonal linear local spline discriminant embedding (O-LLSDE) is proposed for face recognition. Derived from local spline embedding (LSE), O-LLSDE not only inherits the advantages of LSE which uses local tangent space as a representation of the local geometry so as to preserve the local structure, but also makes full use of class information and orthogonal subspace to improve discriminant power. Extensive experiments on standard face databases demonstrate the effectiveness of the proposed method.
Keywords
face recognition; feature extraction; face recognition; feature extraction; local geometry representation; local spline embedding; local tangent space; orthogonal linear local spline discriminant embedding; standard face databases; Equations; Principal component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location
Barcelona
ISSN
1098-7576
Print_ISBN
978-1-4244-6916-1
Type
conf
DOI
10.1109/IJCNN.2010.5596905
Filename
5596905
Link To Document