A study on illumination invariant face recognition methods based on multiple eigenspaces

Authors:
Wujun Li;Chongjun Wang;Dianjiang Xu;Bin Luo;Zhaojian Chen
Affiliations:
National Laboratory for Novel Software Technology, Nanjing University, Nanjing , Jiangshu, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing , Jiangshu, China;Department of Computer Science, North Dakota State University, Fargo ND;National Laboratory for Novel Software Technology, Nanjing University, Nanjing , Jiangshu, China;National Laboratory for Novel Software Technology, Nanjing University, Nanjing , Jiangshu, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

Citing 3
Cited 1

The CMU Pose, Illumination, and Expression (PIE) Database

FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Illumination Invariant Face Recognition Based on Neural Network Ensemble

ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Eigenfaces for recognition

Journal of Cognitive Neuroscience

A multiple eigenspaces constructing method and its application to face recognition

ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents two multiple illumination eigenspaces-based methods, RDEB and BPNNB, for solving the variable illumination problem of face recognition. The experiment shows that the methods have a high recognition ratio. In particular, BPNNB has outperformed the assumptive method which knows the illumination directions of faces and completes recognition in the specific eigenspace using eigenface method[2] for each face subset with a specific illumination direction.