Robust adaptive-scale parametric model estimation for computer vision

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 26, Issue 11, 2004, Pages 1459-1474

  Wang, Hanzi ^a   Suter, David ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

Adaptive least kth order squares; Fundamental matrix estimation; Kernel density estimation; Least median of squares; Mean shift; Random sample consensus; Range image segmentation; Residual consensus; Robust model fitting

Indexed keywords

CURVE FITTING; IMAGE SEGMENTATION; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY DENSITY FUNCTION; RANDOM PROCESSES; STATISTICAL METHODS;

FUNDAMENTAL MATRIX ESTIMATION; KERNEL DENSITY ESTIMATION; RANDOM SAMPLE CONSENSUS; RANGE IMAGE SEGMENTATION; RESIDUAL CONSENSUS; ROBUST MODEL FITTING;

COMPUTER VISION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; COMPUTER SIMULATION; FEEDBACK SYSTEM; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; FEEDBACK; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE; USER-COMPUTER INTERFACE;

EID: 12844289094     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2004.109     Document Type: Article

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