Probabilistic tangent subspace: a unified view
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A Unified Framework for Subspace Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition from a single image per person: A survey
Pattern Recognition
3D Face Recognition by Local Shape Difference Boosting
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
A methodology for rapid illumination-invariant face recognition using image processing filters
Computer Vision and Image Understanding
Fast algorithm for updating the discriminant vectors of dual-space LDA
IEEE Transactions on Information Forensics and Security
An automatic language identification method based on subspace analysis
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Visual object recognition using probabilistic kernel subspace similarity
Pattern Recognition
Selecting discriminant eigenfaces for face recognition
Pattern Recognition Letters
A rank-one update algorithm for fast solving kernel Foley-Sammon optimal discriminant vectors
IEEE Transactions on Neural Networks
Bayesian face recognition using support vector machine and face clustering
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
Frame synchronization and multi-level subspace analysis for video based face recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Video based face recognition using multiple classifiers
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Inter-modality face recognition
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Face recognition from video using the generic shape-illumination manifold
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
A novel Gabor-LDA based face recognition method
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
Grid-Based multi-scale PCA method for face recognition in the large face database
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
Grid-Based parallel elastic graph matching face recognition method
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
Boosting multi-gabor subspaces for face recognition
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Face recognition using neighborhood preserving projections
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part II
Face recognition – combine generic and specific solutions
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Recent advances in subspace analysis for face recognition
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Local feature analysis with class information
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
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We propose a face difference model that decomposesface difference into three components, intrinsicdifference, transformation difference, and noise. Usingthe face difference model and a detailed subspace analysison the three components we develop a unified frameworkfor subspace analysis. Using this framework we discoverthe inherent relationship among different subspacemethods and their unique contributions to the extractionof discriminating information from the face difference.This eventually leads to the construction of a 3Dparameter space that uses three subspace dimensions asaxis. Within this parameter space, we develop a unifiedsubspace analysis method that achieves better recognitionperformance than the standard subspace methods on over2000 face images from the FERET database.