Regression Tree Fields An efficient, non-parametric approach to image labeling problems

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 2376-2383

  Jancsary, Jeremy ^a   Nowozin, Sebastian ^b   Sharp, Toby ^b   Rother, Carsten ^b  

^a VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

^b MICROSOFT RESEARCH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CONDITIONAL RANDOM FIELD; DE-NOISING; ENERGY FUNCTIONS; EXPRESSIVE POWER; GAUSSIAN RANDOM FIELDS; IMAGE LABELING; INPAINTING; JOINT DETECTION; NON-PARAMETRIC REGRESSION; NONPARAMETRIC APPROACHES; ORDERS OF MAGNITUDE; PREDICTIVE PERFORMANCE; REGRESSION TREES; TRAINING DATA; VECTOR VALUED;

COMPUTER VISION; DECISION TREES; FORECASTING; GAUSSIAN DISTRIBUTION; REGRESSION ANALYSIS;

TREES (MATHEMATICS);

EID: 84866674114     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247950     Document Type: Conference Paper

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