Gender classification via global-local features fusion
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Local gradient increasing pattern (LGIP) for facial representation and gender recognition
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Face recognition based on combination of human perception and local binary pattern
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
Texture classification based on BIMF monogenic signals
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Gender Recognition Based On Combining Facial and Hair Features
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Gender Recognition Based On Combining Facial and Hair Features
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Three robust features extraction approaches for facial gender classification
The Visual Computer: International Journal of Computer Graphics
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In this paper, we present a novel texture descriptor Local Directional Pattern (LDP) to represent facial image for gender classification. The face area is divided into small regions, from which LDP histograms are extracted and concatenated into a single vector to efficiently represent the face image. The classification is performed by using support vector machines (SVMs), which had been shown to be superior to traditional pattern classifiers in gender classification problem. Experimental results show the superiority of the proposed method on the images collected from FERET face database and achieved 95.05% accuracy.