Occlusion handling via random subspace classifiers for human detection

IEEE Transactions on Cybernetics

Volumn 44, Issue 3, 2014, Pages 342-354

  Marín, Javier ^a   Vázquez, David ^a   López, Antonio M ^a   Amores, Jaume ^a   Kuncheva, Ludmila I ^b  

^a UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

^b BANGOR UNIVERSITY   (United Kingdom)

Author keywords

Ensemble; human detection; partial occlusions; random subspace classifiers

Indexed keywords

DETECTION PERFORMANCE; ENSEMBLE; HUMAN DETECTION; PARTIAL OCCLUSIONS; PERFORMANCE AND RELIABILITIES; RANDOM SUBSPACE CLASSIFIERS; RANDOM SUBSPACE METHOD; STATE-OF-THE-ART APPROACH;

EXPERIMENTS; SEMANTICS;

DETECTORS;

ALGORITHM; AUTOMATED PATTERN RECOGNITION; BIOMETRY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MACHINE LEARNING; PHOTOGRAPHY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; WHOLE BODY IMAGING;

ALGORITHMS; BIOMETRIC IDENTIFICATION; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MACHINE LEARNING; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PHOTOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; WHOLE BODY IMAGING;

EID: 84896812359     PISSN: 21682267     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCYB.2013.2255271     Document Type: Article

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