The Role of Face Parts in Gender Recognition
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
On the Complementarity of Face Parts for Gender Recognition
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Committee machines for facial-gender recognition
International Journal of Hybrid Intelligent Systems
Face Gender Classification on Consumer Images in a Multiethnic Environment
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Gender Recognition from a Partial View of the Face Using Local Feature Vectors
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Learning local features for age estimation on real-life faces
Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis
Learning local binary patterns for gender classification on real-world face images
Pattern Recognition Letters
Soft biometric classification using local appearance periocular region features
Pattern Recognition
Face-based multiple instance analysis for smart electronics billboard
Multimedia Tools and Applications
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
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In most of the automatic face classification applications, images should be captured in natural environments, where partial occlusions or high local changes in the illumination are frequent. For this reason, face classification tasks in uncontrolled environment are still nowadays unsolved problems, given that the loss of information caused by these artifacts can easily mislead any classifier. We present in this paper a system to extract robust face features that can be applied to encode information from any zone of the face and that can be used for different face classification problems. To test this method we include the results obtained in different gender classification experiments, considering controlled and uncontrolled environments and extracting face features from internal and external face zones. The obtained rates show, on the one hand, that we can obtain significant information applying the presented feature extraction scheme and, on the other hand, that the external face zone can contribute useful information for classification purposes.