Academic Journals Database
Disseminating quality controlled scientific knowledge

Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA

ADD TO MY LIST
 
Author(s): Jian-Gang Wang | Hui Kong | Eric Sung | Wei-Yun Yau | Eam Khwang Teoh

Journal: EURASIP Journal on Image and Video Processing
ISSN 1687-5176

Volume: 2007;
Date: 2007;
Original page

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.
Affiliate Program      Why do you need a reservation system?