EMPATH: face, emotion, and gender recognition using holons
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
SexNet: A neural network identifies sex from human faces
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
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-View Face Alignment Using Direct Appearance Models
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Video parsing based on head tracking and face recognition
Proceedings of the 6th ACM international conference on Image and video retrieval
An experimental comparison of gender classification methods
Pattern Recognition Letters
Fusing gait and face cues for human gender recognition
Neurocomputing
Face Gender Classification on Consumer Images in a Multiethnic Environment
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Facial Gender Classification Using LUT-Based Sub-images and DIE
ICDHM '09 Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009
Facial gender classification using shape-from-shading
Image and Vision Computing
SODA-boosting and its application to gender recognition
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Gender classification in uncontrolled settings using additive logistic models
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Gender discriminating models from facial surface normals
Pattern Recognition
Gender classification of faces using adaboost
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Soft biometric classification using local appearance periocular region features
Pattern Recognition
Face-based multiple instance analysis for smart electronics billboard
Multimedia Tools and Applications
Bag of features using sparse coding for gender classification
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Demographic classification with local binary patterns
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Improving gender recognition using genetic algorithms
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
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There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but are more computation intensive while Adaboost ones are much faster with slightly worse performance. For possible real-time applications the Adaboost method seems a better choice. However, the existing Adaboost algorithms take simple threshold weak classifiers, which are too weak to fit complex distributions, as the hypothesis space. Because of this limitation of the hypothesis model, the training procedure is hard to converge. This paper presents a novel Look Up Table (LUT) weak classifier based Adaboost approach to learn gender classifier. This algorithm converges quickly and results in efficient classifiers. The experiments and analysis show that the LUT weak classifiers are more suitable for boosting procedure than threshold ones.