Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 20, Issue 1, Pages 247-256Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2010.2060207
Keywords
Conditional mutual information (CMI); face recognition; Gabor volume based local binary pattern (GV-LBP); Gabor volume representation; local binary pattern (LBP)
Funding
- Chinese National Hi-Tech (863) Program [2008AA01Z124]
- National Science and Technology Support Program [2009BAK43B26]
- AuthenMetric RD Fund
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Information jointly contained in image space, scale and orientation domains can provide rich important clues not seen in either individual of these domains. The position, spatial frequency and orientation selectivity properties are believed to have an important role in visual perception. This paper proposes a novel face representation and recognition approach by exploring information jointly in image space, scale and orientation domains. Specifically, the face image is first decomposed into different scale and orientation responses by convolving multiscale and multi-orientation Gabor filters. Second, local binary pattern analysis is used to describe the neighboring relationship not only in image space, but also in different scale and orientation responses. This way, information from different domains is explored to give a good face representation for recognition. Discriminant classification is then performed based upon weighted histogram intersection or conditional mutual information with linear discriminant analysis techniques. Extensive experimental results on FERET, AR, and FRGC ver 2.0 databases show the significant advantages of the proposed method over the existing ones.
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