SexNet: A neural network identifies sex from human faces
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Gender with Support Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Unified Learning Framework for Real Time Face Detection and Classification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Multi-Modal 2D and 3D Biometrics for Face Recognition
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Gender Recognition from Walking Movements using Adaptive Three-Mode PCA
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
Handbook of Face Recognition
Curse of mis-alignment in face recognition: problem and a novel mis-alignment learning solution
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Mixture of experts for classification of gender, ethnic origin, and pose of human faces
IEEE Transactions on Neural Networks
Facial Gender Classification Using Shape from Shading and Weighted Principal Geodesic Analysis
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Supervised Principal Geodesic Analysis on Facial Surface Normals for Gender Classification
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Fuzzy 3D Face Ethnicity Categorization
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
A Pruning Approach Improving Face Identification Systems
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Facial gender classification using shape-from-shading
Image and Vision Computing
Weighted principal geodesic analysis for facial gender classification
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Gender and ethnicity identification from silhouetted face profiles
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Extracting gender discriminating features from facial needle-maps
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques
International Journal of Computer Vision
Supervised relevance maps for increasing the distinctiveness of facial images
Pattern Recognition
Gender discriminating models from facial surface normals
Pattern Recognition
Gender classification using the profile
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Distinguishing Facial Features for Ethnicity-Based 3D Face Recognition
ACM Transactions on Intelligent Systems and Technology (TIST)
Soft biometric classification using local appearance periocular region features
Pattern Recognition
Demographic classification with local binary patterns
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
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Human faces provide demographic information, such as gender and ethnicity. Different modalities of human faces, e.g., range and intensity, provide different cues for gender and ethnicity identifications. In this paper we exploit the range information of human faces for ethnicity identification using a support vector machine. An integration scheme is also proposed for ethnicity and gender identifications by combining the registered range and intensity images. The experiments are conducted on a database containing 1240 facial scans of 376 subjects. It is demonstrated that the range modality provides competitive discriminative power on ethnicity and gender identifications to the intensity modality. For both gender and ethnicity identifications, the proposed integration scheme outperforms each individual modality.