Title
Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA.
Abstract
This paper presents a novel approach for face recognition based on the fusion of the appearance and depth information at the match score level. We apply passive stereoscopy instead of active range scanning as popularly used by others. We show that present-day passive stereoscopy, though less robust and accurate, does make positive contribution to face recognition. By combining the appearance and disparity in a linear fashion, we verified experimentally that the combined results are noticeably better than those for each individual modality. We also propose an original learning method, the bilateral two-dimensional linear discriminant analysis (B2DLDA), to extract facial features of the appearance and disparity images. We compare B2DLDA with some existing 2DLDA methods on both XM2VTS database and our database. The results show that the B2DLDA can achieve better results than others.
Year
DOI
Venue
2007
10.1155/2007/38205
EURASIP J. Image and Video Processing
Keywords
Field
DocType
linear fashion,face recognition,bilateral two-dimensional linear discriminant,passive stereoscopy,better result,appearance image,disparity image,passive stereo depth map,combined result,present-day passive stereoscopy,xm2vts database,active range,depth map
Computer vision,Facial recognition system,Pattern recognition,Three-dimensional face recognition,Computer science,Stereoscopy,Fusion,Artificial intelligence,Linear discriminant analysis,Biometrics,Depth map
Journal
Volume
Issue
ISSN
2007
2
1687-5281
Citations 
PageRank 
References 
4
0.42
29
Authors
5
Name
Order
Citations
PageRank
Jiangang Wang160940.59
Hui Kong2102.25
Eric Sung330116.57
Wei-Yun Yau4123398.01
Eam Khwang Teoh587189.16