Dynamic graph cuts for efficient inference in Markov random fields

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 29, Issue 12, 2007, Pages 2079-2088

  Kohli, Pushmeet ^a   Torr, Philip H S ^a  

^a OXFORD BROOKES UNIVERSITY   (United Kingdom)

Author keywords

Dynamic graph cuts; Energy minimization; Markov random fields; Maximum flow; st mincut; Video segmentation

Indexed keywords

ALGORITHMS; COMPUTER VISION; GRAPHIC METHODS; MARKOV PROCESSES;

DYNAMIC ALGORITHM; MARKOV RANDOM FIELD; OBJECT-BACKGROUND SEGMENTATION; VIDEO SEGMENTATION;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; PROBABILITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MARKOV CHAINS; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 36249013608     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.1128     Document Type: Article

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