SexNet: A neural network identifies sex from human faces
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Learning Gender with Support Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gender and Ethnic Classification of Face Images
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Age and Gender Estimation Based on Wrinkle Texture and Color of Facial Images
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
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
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
Boosting Nested Cascade Detector for Multi-View Face Detection
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A Local Region-based Approach to Gender Classi.cation From Face Images
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Are External Face Features Useful for Automatic Face Classification?
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
An Experimental Study on Automatic Face Gender Classification
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Gender Recognition in Non Controlled Environments
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
LUT-based Adaboost for gender classification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Mixture of experts for classification of gender, ethnic origin, and pose of human faces
IEEE Transactions on Neural Networks
Demographic classification with local binary patterns
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Learning local features for age estimation on real-life faces
Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis
Dynamic estimation of family relations from photos
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Gender classification using the profile
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Gender classification via global-local features fusion
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Learning local binary patterns for gender classification on real-world face images
Pattern Recognition Letters
On the importance of multi-dimensional information in gender estimation from face images
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Soft biometric classification using local appearance periocular region features
Pattern Recognition
Image and Vision Computing
Recognizing human gender in computer vision: a survey
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Robust gender recognition by exploiting facial attributes dependencies
Pattern Recognition Letters
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In this paper, we target at face gender classification on consumer images in a multiethnic environment. The consumer images are much more challenging, since the faces captured in the real situation vary in pose, illumination and expression in a much larger extent than that captured in the constrained environments such as the case of snapshot images. To overcome the non-uniformity, a robust Active Shape Model (ASM) is used for face texture normalization. The probabilistic boosting tree approach is presented which achieves a more accurate classification boundary on consumer images. Besides that, we also take into consideration the ethnic factor in gender classification and prove that ethnicity specific gender classifiers could remarkably improve the gender classification accuracy in a multiethnic environment. Experiments show that our methods achieve better accuracy and robustness on consumer images in a multiethnic environment.