Dynamic trees for unsupervised segmentation and matching of image regions

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 27, Issue 11, 2005, Pages 1762-1777

  Todorovic, Sinisa ^a   Nechyba, Michael C ^b  

^a University of Florida   (United States)

^b Pittsburgh Pattern Recognition   (United States)

Author keywords

Bayesian networks; Dynamic trees; Generative models; Image matching; Object recognition; Variational inference image segmentation

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; CONVERGENCE OF NUMERICAL METHODS; IMAGE SEGMENTATION; MATHEMATICAL MODELS; PATTERN MATCHING; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS; TREES (MATHEMATICS);

BAYESIAN NETWORKS; DYNAMIC TREES; GENERATIVE MODELS; IMAGE REGIONS; STRUCTURED VARIATIONAL APPROXIMATION (SVA); UNSUPERVISED SEGMENTATION; VARIATIONAL INFERENCE;

OBJECT RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 28044459862     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2005.219     Document Type: Article

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