A massively parallel face recognition system
EURASIP Journal on Embedded Systems
A comparative study of Minimax Probability Machine-based approaches for face recognition
Pattern Recognition Letters
Eigenface vs. Spectroface: a comparison on the face recognition problems
SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
Face recognition in non-uniform illumination conditions using lighting normalization and SVM
CEA'07 Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and Applications
Face recognition using HOG-EBGM
Pattern Recognition Letters
Detection and tracking of humans and faces
Journal on Image and Video Processing - Regular
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Recognition of faces in unconstrained environments: a comparative study
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Centroid neural network for face recognition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Eigenface vs. Spectroface: a comparison on the face recognition problems
SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
Face recognition using PCA and SVM
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Bimodal biometric person identification system under perturbations
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Face recognition using a color PCA framework
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Studies on hyperspectral face recognition in visible spectrum with feature band selection
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Variable lighting face recognition using discrete wavelet transform
Pattern Recognition Letters
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Gradient-based local descriptor and centroid neural network for face recognition
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Two dimensional synthetic face generation and verification using set estimation technique
Computer Vision and Image Understanding
Separability oriented preprocessing for illumination-insensitive face recognition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Machine Vision and Applications
Low-resolution face recognition: a review
The Visual Computer: International Journal of Computer Graphics
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Eigenspace-based face recognition corresponds to one of the most successful methodologies for the computational recognition of faces in digital images. Starting with the Eigenface-Algorithm, different eigenspace-based approaches for the recognition of faces have been proposed. They differ mostly in the kind of projection method used (standard, differential, or kernel eigenspace), in the projection algorithm employed, in the use of simple or differential images before/after projection, and in the similarity matching criterion or classification method employed. The aim of this paper is to present an independent comparative study among some of the main eigenspace-based approaches. We believe that carrying out independent studies is relevant, since comparisons are normally performed using the implementations of the research groups that have proposed each method, which does not consider completely equal working conditions for the algorithms. Very often, a contest between the abilities of the research groups rather than a comparison between methods is performed. This study considers theoretical aspects as well as simulations performed using the Yale Face Database, a database with few classes and several images per class, and FERET, a database with many classes and few images per class.