Algorithms for clustering data
Algorithms for clustering data
Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Human face recognition and the face image set's topology
CVGIP: Image Understanding
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
“Rough enough”—a system supporting the rough sets approach
SCAI '97 Proceedings of the sixth Scandinavian conference on Artificial intelligence
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition by elastic bunch graph matching
Intelligent biometric techniques in fingerprint and face recognition
Unsupervised Feature Selection Using Feature Similarity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A Bayesian Approach to Joint Feature Selection and Classifier Design
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous Feature Selection and Clustering Using Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Subset Selection and Ranking for Data Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using rough set in feature selection and reduction in face recognition problem
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Evolutionary Rough Feature Selection in Gene Expression Data
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Real-time face detection and lip feature extraction using field-programmable gate arrays
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Elastic Bunch Graph Matching is a feature-based face recognition algorithm which has been used to determine facial attributes from an image. However the dimension of the feature vectors, in case of EBGM, is quite high. Feature selection is a useful preprocessing step for reducing dimensionality, removing irrelevant data, improving learning accuracy and enhancing output comprehensibility. In rough set theory reducts are the minimal subsets of attributes that are necessary and sufficient to represent a correct decision about classification. The high complexity of the problem has motivated investigators to apply various approximation techniques like the multi-objective GAs to find near optimal solutions for reducts. We present here an application of the evolutionary-rough feature selection algorithm to the face recognition problem. The input corresponds to biometric features, modeled as Gabor jets at each node of the EBGM. Reducts correspond to feature subsets of reduced cardinality, for efficiently discriminating between the faces. The whole process is optimized using MOGA. The simulation is performed on large number of Caucasian and Indian faces, using the FERET and CDAC databases. The merit of clustering and their optimality is determined using cluster validity indices. Successful retrieval of faces is also performed.