Motion estimation using statistical learning theory

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 26, Issue 4, 2004, Pages 466-478

  Wechsler, Harry ^a   Duric, Zoran ^a   Li, Fayin ^a   Cherkassky, Vladimir ^b  

^a George Mason University   (United States)

^b University of Minnesota   (United States)

Author keywords

Aperture problem; Complexity control; Condition number; Image flow; Model selection; Motion estimation; Robust learning; Statistical learning theory; Tracking; Visual motion

Indexed keywords

EXTRAPOLATION; INTERPOLATION; LEARNING SYSTEMS; MATHEMATICAL MODELS; OPTIMIZATION; STATISTICAL METHODS;

APERTURE PROBLEM; COMPLEXITY CONTROL; IMAGE FLOW; STATISTICAL LEARNING THEORY; VISUAL MOTION;

MOTION ESTIMATION;

ALGORITHM; ARM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; MOTION; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; ARM; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MOTION; MOVEMENT; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 1842530929     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2004.1265862     Document Type: Article

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