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A dissimilarity kernel with local features for robust facial recognition
2010
2010 IEEE International Conference on Image Processing
Local binary pattern (LBP) has recently been proposed for texture analysis and local feature description and has also been applied to face recognition with promising results. However, besides the descriptors, a suitable similarity measure that can efficiently learn to distinguish facial features is also important. In this paper, a novel framework for robust face recognition is presented that considers both local and global features by using multi-resolution LBP descriptors. The framework can
doi:10.1109/icip.2010.5653495
dblp:conf/icip/HuangY10
fatcat:i4whell2enbyzmcz7ff47jmsgu