IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Classification of Single Facial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Organizing Maps
Concurrent Self-Organizing Maps for Pattern Classification
ICCI '02 Proceedings of the 1st IEEE International Conference on Cognitive Informatics
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Training of Classifiers Using Virtual Samples Only
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
MMES'10 Proceedings of the 2010 international conference on Mathematical models for engineering science
k-nearest neighbors directed noise injection in multilayer perceptron training
IEEE Transactions on Neural Networks
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The most expressive way humans display emotions is through facial expressions. This paper is dedicated to the challenging computer vision task of subject-independent emotion recognition from facial expressions. The original key idea of the proposed model is the increasing of the neural classifier training set size by adding "virtual" samples generated with a system of Concurrent Self-Organizing Maps (CSOM). The model consists of the following main processing cascade: (a) Gabor Wavelet Filtering (GVF); (b) dimensionality reduction using Principal Component Analysis (PCA); (c) Radial Basis Function (RBF) neural classifier trained with virtual samples generated by CSOM system (VSG-CSOM). We have evaluated the above proposed model for person-independent facial expression recognition using JAFFE database. One obtains an average recognition score for the test set (leave-one subject out test method) of 69.70%. The advantage of using CSOM-VSG-RBF over a traditional RBF neural classifier means an improvement of recognition score with about 16% (from 53.44% for RBF to 69.70% for VSG-CSOM-RBF).