Face recognition with salient local gradient orientation binary patterns

Authors:
Shu Liao;Albert C. S. Chung
Affiliations:
Lo Kwee-Seong Medical Image Analysis Laboratory, Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong;Lo Kwee-Seong Medical Image Analysis Laboratory, Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

This paper proposes a new face recognition method. There are two novelties in the proposed method. First, a new saliency measure function is designed to detect the most salient regions in facial images and determine their corresponding best scales. Second, a new type of image feature, called local gradient orientation binary pattern (LGOBP) is proposed, which captures the neighborhood gradient orientation information which is not considered in the conventional local binary patterns (LBP) to give more discriminant power. LGOBPs are extracted from the most salient regions selected by the proposed saliency measure function. The proposed method is evaluated on the FRGC version 2 database by comparing it with several widely used methods. Experimental results show that the proposed method achieves the highest recognition rate among all the compared methods.