Machine Learning
Classifying Facial Attributes Using a 2-D Gabor Wavelet and Discriminant Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Gender Classification with Support Vector Machines
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
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
Face recognition using gender information
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
Bag of soft biometrics for person identification
Multimedia Tools and Applications
Gender recognition using a min-max modular support vector machine
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Multi-view gender classification using local binary patterns and support vector machines
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Vision-Based face understanding technologies and their applications
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Soft biometric classification using local appearance periocular region features
Pattern Recognition
A methodological framework for investigating age factors on the performance of biometric systems
Proceedings of the on Multimedia and security
Demographic classification with local binary patterns
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Ethnicity classification based on a hierarchical fusion
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Improving gender recognition using genetic algorithms
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
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We have advanced efforts to develop vision based human understanding technologies for realizing human-friendly machine interfaces. Visual information, such as gender, age ethnicity, and facial expression play an important role in face-to-face communication. This paper addresses a novel approach for ethnicity classification with facial images. In this approach, Gabor Wavelets Transformation and retina sampling are combined to extract key facial features, and support vector machines are used for ethnicity classification. Our system, based on this approach, achieved approximately 94% for ethnicity estimation under various lighting conditions.