Supervised orthogonal discriminant subspace projects learning for face recognition

Neural Networks

Volumn 50, Issue , 2014, Pages 33-46

  Chen, Yu ^a   Xu, Xiao Hong ^a  

^a SOUTH CHINA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Dimensionality reduction; Face recognition; Maximum margin criterion; Orthogonal constraint; Small sample size

Indexed keywords

ALGORITHMS; MATRIX ALGEBRA;

DIMENSIONALITY REDUCTION; HIGH DIMENSIONAL DATA; LINEAR DIMENSION REDUCTION; MAXIMUM MARGIN CRITERIONS; NEIGHBORHOOD STRUCTURE; ORTHOGONAL CONSTRAINTS; SMALL SAMPLE SIZE; SMALL SAMPLE SIZE PROBLEMS;

FACE RECOGNITION;

ARTICLE; AUTOMATED PATTERN RECOGNITION; CONTROLLED STUDY; DATA BASE; FACE RECOGNITION; FACIAL EXPRESSION; HUMAN; IMAGE ANALYSIS; LEARNING ALGORITHM; MATHEMATICAL ANALYSIS; MULTIFACTOR DIMENSIONALITY REDUCTION; ORTHOGONAL ROTATION; PRIORITY JOURNAL; SAMPLE SIZE; STATISTICAL SIGNIFICANCE; SUPERVISED ORTHOGONAL DISCRIMINANT SUBSPACE PROJECTION; VISUAL MEMORY;

DIMENSIONALITY REDUCTION; FACE RECOGNITION; MAXIMUM MARGIN CRITERION; ORTHOGONAL CONSTRAINT; SMALL SAMPLE SIZE;

ALGORITHMS; BIOMETRY; DISCRIMINATION (PSYCHOLOGY); FACE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LEARNING; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; PATTERN RECOGNITION, VISUAL; RECOGNITION (PSYCHOLOGY);

EID: 84887745017     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2013.10.006     Document Type: Article

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