Learning the best subset of local features for face recognition

Authors:
Berk Gökberk;M. Okan İrfanoğlu;Lale Akarun;Ethem Alpaydın
Affiliations:
Department of Computer Engineering, Boğaziçi University, TR-34342, Bebek, Istanbul, Turkey;Department of Computer Engineering, Boğaziçi University, TR-34342, Bebek, Istanbul, Turkey;Department of Computer Engineering, Boğaziçi University, TR-34342, Bebek, Istanbul, Turkey;Department of Computer Engineering, Boğaziçi University, TR-34342, Bebek, Istanbul, Turkey
Venue:
Pattern Recognition
Year:
2007

Citing 12
Cited 5

Face Recognition by Elastic Bunch Graph Matching

IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review

IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary Pursuit and Its Application to Face Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
PCA versus LDA

IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Support Vector Machines to Enhance the Performance of Elastic Graph Matching for Frontal Face Authentication

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Selective Attention-Based Method for Visual Pattern Recognition with Application to Handwritten Digit Recognition and Face Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Manifolds and Probabilistic Subspaces for Visual Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Optimal Non-Orthogonal Wavelet Basis Evaluated by Information Complexity

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Feature Selection for Pose Invariant Face Recognition

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Optimal sampling of Gabor features for face recognition

Pattern Recognition Letters
Recent advances in visual and infrared face recognition: a review

Computer Vision and Image Understanding
Face recognition using ada-boosted gabor features

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition

Implications of ceiling effects in defect predictors

Proceedings of the 4th international workshop on Predictor models in software engineering
Evolutionary learning of local descriptor operators for object recognition

Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A new algorithm for age recognition from facial images

Signal Processing
Methodological improvement on local Gabor face recognition based on feature selection and enhanced Borda count

Pattern Recognition
Pixel selection based on discriminant features with application to face recognition

Pattern Recognition Letters

Quantified Score

Hi-index	0.01

Visualization

Abstract

We propose a novel, local feature-based face representation method based on two-stage subset selection where the first stage finds the informative regions and the second stage finds the discriminative features in those locations. The key motivation is to learn the most discriminative regions of a human face and the features in there for person identification, instead of assuming a priori any regions of saliency. We use the subset selection-based formulation and compare three variants of feature selection and genetic algorithms for this purpose. Experiments on frontal face images taken from the FERET dataset confirm the advantage of the proposed approach in terms of high accuracy and significantly reduced dimensionality.