Extended locally linear embedding with gabor wavelets for face recognition

Authors:
Zhonglong Zheng;Jie Yang;Xu Qing
Affiliations:
Institute of image processing and pattern recognition, Shanghai Jiao Tong University, Shanghai, China;Institute of image processing and pattern recognition, Shanghai Jiao Tong University, Shanghai, China;Institute of image processing and pattern recognition, Shanghai Jiao Tong University, Shanghai, China
Venue:
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Year:
2004

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Abstract

Many current face recognition algorithms are based on face representations found by unsupervised statistical methods One of the fundamental problems of face recognition is dimensionality reduction Principal component analysis is a well-known linear method for reducing dimension Recently, locally linear embedding (LLE) is proposed as an unsupervised procedure for mapping higher-dimensional data nonlinearly to a lower-dimensional space This method, when combined with fisher linear discriminant models, is called extended LLE (ELLE) in this paper Furthermore, the ELLE yields good classification results in the experiments Also, we apply the Gabor wavelets as a pre-processing method which contributes a lot to the final results because it deals with the detailed signal of an image and is robust to light variation Numerous experiments on ORL and AR face data sets have shown that our algorithm is more effective than the original LLE and is insensitive to light variation.