Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2007 Article ID 38205 11 pages doi 2007 38205 Research Article Fusion of Appearance Image and Passive Stereo Depth Map for Face Recognition Based on the Bilateral 2DLDA Jian-Gang Wang 1 Hui Kong 2 Eric Sung 2 Wei-Yun Yau 1 and Eam Khwang Teoh2 1 Institute for Infocomm Research 21 Heng Mui Keng Terrace Singapore 119613 2 School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Received 27 April 2006 Revised 22 October 2006 Accepted 18 June 2007 Recommended by Christophe Garcia 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. Copyright 2007 Jian-Gang Wang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION A great amount of research effort has been devoted to face recognition based on 2D face images 1 . However the methods developed are sensitive to the changes in pose illumination and face expression. A robust .
