Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Updating Problems in Latent Semantic Indexing
SIAM Journal on Scientific Computing
Unified Subspace Analysis for Face Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
IDR/QR: an incremental dimension reduction algorithm via QR decomposition
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A Unified Framework for Subspace Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Face Recognition Using Gram-Schmidt Orthogonalization for LDA
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Object Tracking Using Incremental Fisher Discriminant Analysis
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Discriminative Common Vectors for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Random Sampling for Subspace Face Recognition
International Journal of Computer Vision
Comments on the Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion
The Journal of Machine Learning Research
Random sampling LDA for face recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Dual-space linear discriminant analysis for face recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Incremental linear discriminant analysis for classification of data streams
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Incremental Linear Discriminant Analysis for Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An optimization criterion for generalized discriminant analysis on undersampled problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
On self-organizing algorithms and networks for class-separability features
IEEE Transactions on Neural Networks
Artificial neural networks for feature extraction and multivariate data projection
IEEE Transactions on Neural Networks
Face recognition based on the multi-scale local image structures
Pattern Recognition
Incremental complete LDA for face recognition
Pattern Recognition
Incremental learning of complete linear discriminant analysis for face recognition
Knowledge-Based Systems
Hi-index | 0.00 |
Dual-space linear discriminant analysis (DSLDA) is a popular method for discriminant analysis. The basic idea of the DSLDA method is to divide the whole data space into two complementary subspaces, i.e., the range space of the within-class scatter matrix and its complementary space, and then solve the discriminant vectors in each subspace. Hence, the DSLDA method can take full advantage of the discriminant information of the training samples. However, from the computational point of view, the original DSLDA method may not be suitable for online training problems because of its heavy computational cost. To this end, we modify the original DSLDA method and then propose a data order independent incremental algorithm to accurately update the discriminant vectors of the DSLDA method when new samples are inserted into the training data set. We conduct experiments on the AR face database to confirm the better performance of the proposed algorithms in terms of the recognition accuracy and computational efficiency.