The nature of statistical learning theory
The nature of statistical learning theory
Learning Gender with Support Faces
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
PCA for Gender Estimation: Which Eigenvectors Contribute?
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Face Detection Using Improved LBP under Bayesian Framework
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Ethnicity estimation with facial images
FGR' 04 Proceedings of the Sixth IEEE 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
An experimental comparison of gender classification methods
Pattern Recognition Letters
A Framework for Multi-view Gender Classification
Neural Information Processing
Combining appearance and motion for face and gender recognition from videos
Pattern Recognition
RVM-based human action classification in crowd through projection and star skeletonization
Journal on Image and Video Processing - Special issue on video-based modeling, analysis, and recognition of human motion
Personal identification using periocular skin texture
Proceedings of the 2010 ACM Symposium on Applied Computing
Gender classification in uncontrolled settings using additive logistic models
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Selecting optimal orientations of Gabor wavelet filters for facial image analysis
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Multi-view gender classification using hierarchical classifiers structure
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Can gender be predicted from near-infrared face images?
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Gender classification via global-local features fusion
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Recognizing human gender in computer vision: a survey
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Understanding critical factors in appearance-based gender categorization
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Improving gender recognition using genetic algorithms
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
Elliptical local binary patterns for face recognition
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
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In this paper, we present a novel approach to multi-view gender classification considering both shape and texture information to represent facial image. The face area is divided into small regions, from which local binary pattern(LBP) histograms are extracted and concatenated into a single vector efficiently representing the facial 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. The experiments clearly show the superiority of the proposed method over support gray faces on the CAS-PEAL face database and a highest correct classification rate of 96.75% is obtained. In addition, the simplicity of the proposed method leads to very fast feature extraction, and the regional histograms and global description of the face allow for multi-view gender classification.