Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fragment-Based Approach to Object Representation and Classification
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Object Recognition with Informative Features and Linear Classification
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
An assembled matrix distance metric for 2DPCA-based image recognition
Pattern Recognition Letters
Non-iterative generalized low rank approximation of matrices
Pattern Recognition Letters
Is two-dimensional PCA equivalent to a special case of modular PCA?
Pattern Recognition Letters
Volume measure in 2DPCA-based face recognition
Pattern Recognition Letters
Palmprint recognition with improved two-dimensional locality preserving projections
Image and Vision Computing
Classification of multivariate time series using two-dimensional singular value decomposition
Knowledge-Based Systems
A simplified GLRAM algorithm for face recognition
Neurocomputing
Robust Simultaneous Low Rank Approximation of Tensors
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Improving the interest operator for face recognition
Expert Systems with Applications: An International Journal
Modular image principal component analysis for face recognition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Real-time subspace-based background modeling using multi-channel data
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Random subspace two-dimensional PCA for face recognition
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Face recognition in global harmonic subspace
IEEE Transactions on Information Forensics and Security
Palmprint verification using GridPCA for Gabor features
Proceedings of the Second Symposium on Information and Communication Technology
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
A novel feature extraction approach to face recognition based on partial least squares regression
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Block principal component analysis with L1-norm for image analysis
Pattern Recognition Letters
(2D)2 DLDA for efficient face recognition
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Probabilistic learning of similarity measures for tensor PCA
Pattern Recognition Letters
Expert Systems: The Journal of Knowledge Engineering
A unified view of two-dimensional principal component analyses
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Face recognition by using overlapping block discriminative common vectors
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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The state-of-the-art in human face recognition is the subspace methods originated by the Principal Component Analysis (PCA), the Eigenfaces of the facial images. Recently, a technique called Two-dimensional PCA (2DPCA) was proposed for human face representation and recognition. It was developed for image feature extraction based on 2D matrices as opposed to the standard PCA, which is based on 1D vectors. In this note, we show that 2DPCA is equivalent to a special case of an existing feature extraction method, block-based PCA, which has been used for face recognition in a number of systems.