Sign language spotting with a threshold model based on conditional random fields

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 31, Issue 7, 2009, Pages 1264-1277

  Yang, Hee Deok ^a   Sclaroff, Stan ^b   Lee, Seong Whan ^a  

^a Korea University   (South Korea)

^b BOSTON UNIVERSITY   (United States)

Author keywords

Conditional random field; Sign language recognition; Sign language spotting; Threshold model

Indexed keywords

ADAPTIVE THRESHOLDS; APPEARANCE BASED; CONDITIONAL RANDOM FIELD; CONTINUOUS DATA; ERROR RATE; NOVEL METHODS; REASONING METHODS; RECOGNITION RATES; SIGN DETECTION; SIGN DETECTOR; SIGN LANGUAGE; SIGN LANGUAGE RECOGNITION; SIGN LANGUAGE SPOTTING; THRESHOLD MODEL; VERIFICATION METHOD;

IMAGE SEGMENTATION;

LINGUISTICS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGN LANGUAGE; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGN LANGUAGE; SUBTRACTION TECHNIQUE;

EID: 67349252145     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.172     Document Type: Article

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