Learning for stereo vision using the structured support vector machine

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Li, Yunpeng ^a   Huttenlocher, Daniel P ^a  

^a Department of Computer Science and School of Operations Research and Information Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BENCHMARKING; COMPUTER VISION; COST FUNCTIONS; EDGE DETECTION; EDUCATION; FEATURE EXTRACTION; IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGE RETRIEVAL; LABELING; LEARNING ALGORITHMS; LEARNING SYSTEMS; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES; VECTORS;

GRAPH STRUCTURES; HAND TUNING; IMAGE SETS; LEARNING APPROACHES; LOSS FUNCTIONS; MODEL PERFORMANCE; NOISY IMAGES; NON-PARAMETRIC; PROBABILISTIC FRAMEWORKS; RANDOM FIELD; RANDOM-FIELD MODELS; STRUCTURED SUPPORTS;

STEREO VISION;

EID: 51949111559     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587699     Document Type: Conference Paper

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