Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Solving the Small Sample Size Problem of LDA
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
The random electrode selection ensemble for EEG signal classification
Pattern Recognition
The random electrode selection ensemble for EEG signal classification
Pattern Recognition
Multiple feature fusion by subspace learning
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Weighting Individual Classifiers by Local Within-Class Accuracies
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Ensembles of Feature Subspaces for Object Detection
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Local within-class accuracies for weighting individual outputs in multiple classifier systems
Pattern Recognition Letters
Face recognition via AAM and multi-features fusion on riemannian manifolds
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Integration of multi-feature fusion and dictionary learning for face recognition
Image and Vision Computing
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LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA classifier constructed from the small training set is often biased and unstable. In this paper, we use the random subspace method (RSM) to overcome the small sample size problem for LDA. Some low dimensional subspaces are randomly generated from face space. A LDA classifier is constructed from each random subspace, and the outputs of multiple LDA classifiers are combined in the final decision. Based on the random subspace LDA classifiers, a robust face recognition system is developed integrating shape, texture, and Gabor wavelet responses. The algorithm achieves 99.83% accuracy on the XM2VTS database.