Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64339
Title: Two dimensional laplacianfaces method for face recognition
Authors: Niu, B
Shiu, CKS 
Pal, SK
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), v. 4259, p. 852-861 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: In this paper we propose the two dimensional Laplacianfaces method for face recognition. The new algorithm is developed based on the two techniques, i.e., locality preserved embedding and image based projection. The two dimensional Laplacianfaces method is not only computationally more efficient but also more accurate than the one dimensional Laplacianfaces method in extracting the facial features for human face authentication. Extensive experiments are performed to test and evaluate the new algorithm using the Yale and the AR face databases. The experimental results indicate that the two dimensional Laplacianfaces method significantly outperforms the existing two dimensional Eigenfaces, the two dimensional Fisherfaces and the one dimensional Laplacianfaces methods under the various settings of experiment conditions.
Description: The Fifth International Conference on Rough Sets and Current Trends in Computing, RSCTC 2006, Kobe, Japan, 6-8, November, 2006
URI: http://hdl.handle.net/10397/64339
ISBN: 978-3-540-49842-1 (eBook)
978-3-540-47693-1 (softcover)
ISSN: 0302-9743
EISSN: 1611-3349
Appears in Collections:Conference Paper

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