Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Redundant Class-Dependence Feature Analysis Based on Correlation Filters Using FRGC2.0 Data
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Journal of Cognitive Neuroscience
The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Theory and applications of optimized correlation output filters
Theory and applications of optimized correlation output filters
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In this paper, a novel unconstrained correlation filter called Unconstrained Optimal Origin Tradeoff Filter (UOOTF) is presented and applied to face recognition. Compared with the conventional correlation filters in Class-dependence Feature Analysis (CFA), UOOTF increases the overall performance for unseen patterns by removing the hard constraints on the outputs during the filter design. Experimental results on the popular FERET, FRGC and CAS-PEAL R1 face databases show the effectiveness of the proposed unconstrained correlation filter.