Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Local Binary Patterns as an Image Preprocessing for Face Authentication
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Boosting local binary pattern (LBP)-Based face recognition
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
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Local binary patterns (LBP) histogram has gained popularity as face descriptor. However, LBP is limited by its high dimensionality (256). The uniform local binary patterns (ULBP) reduces dimension to 59 at the price of sacrificed performance. In practice, both LBP and ULBP use neighbourhood with no more than eight pixels. This paper proposes a concept named increasing intensity vector (IIV), which specifies local intensity increasing tendency. Based on IIV, two novel local features are proposed: 1) local binary IIV (LBIIV), which extracts IIV from a binarised neighbourhood; 2) local ternary IIV (LTIIV), where the extracted IIV is expressed in ternary mode. Compared to LBP and ULBP, LBIIV has ever fewer patterns (37) without degrading performance, and greatly improves efficiency. Meanwhile, using larger neighbourhood becomes practical. LTIIV then studies an insight into ternary concept of local pattern. Face recognition experiments show that LBIIV and LTIIV outperform LBP and ULBP in accuracy and efficiency.