Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machines applied to face recognition
Proceedings of the 1998 conference on Advances in neural information processing systems II
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator
FCRC '96/WACG '96 Selected papers from the Workshop on Applied Computational Geormetry, Towards Geometric Engineering
Face Recognition Using Kernel Based Fisher Discriminant Analysis
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Discriminative Common Vectors for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recent advances in visual and infrared face recognition: a review
Computer Vision and Image Understanding
IR and visible light face recognition
Computer Vision and Image Understanding
MutualBoost learning for selecting Gabor features for face recognition
Pattern Recognition Letters
Active Shape Models with Invariant Optimal Features: Application to Facial Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Visual object recognition using probabilistic kernel subspace similarity
Pattern Recognition
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Improving the accuracy of suicide attempter classification
Artificial Intelligence in Medicine
Sparse similarity-based fisherfaces
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Hi-index | 0.10 |
In this article, a face recognition algorithm aimed at mimicking the human ability to differentiate people is proposed. For each individual, we first compute a projection line that maximizes his or her dissimilarity to all other people in the user database. Facial identity is thus encoded in the dissimilarity pattern composed by all the projection coefficients of an individual against all other enrolled user identities. Facial recognition is achieved by calculating the dissimilarity pattern of an unknown individual with that of each enrolled user. As the proposed algorithm is composed of different one-dimensional projection lines, it easily allows adding or removing users by simply adding or removing the corresponding projection lines in the system. Ideally, to minimize the influence of these additions/removals, the user group should be representative enough of the general population. Experiments on three widely used databases (XM2VTS, AR and Equinox) show consistently good results. The proposed algorithm achieves Equal Error Rate (EER) and Half-Total Error Rate (HTER) values in the ranges of 0.41-1.67% and 0.1-1.95%, respectively. Our approach yields results comparable to the top two winners in recent contests reported in the literature.