Scalable real-time object recognition and segmentation via cascaded, discriminative Markov random fields

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2010, Pages 3102-3107

  Vernaza, Paul ^a   Lee, Daniel D ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ACCURACY; ERROR-CORRECTING OUTPUT CODING; GRAPH CUT; IMAGE FEATURES; IMAGE REGIONS; LEARNING PROBLEM; LINEAR FUNCTIONS; LOCAL METHODS; MARKOV RANDOM FIELD MODEL; MARKOV RANDOM FIELDS; MULTI-CLASS; OBJECT CLASS; REAL-TIME OBJECT RECOGNITION;

COMPUTATIONAL COMPLEXITY; CONVEX OPTIMIZATION; IMAGE SEGMENTATION; ROBOTICS; STRUCTURAL FRAMES;

OBJECT RECOGNITION;

EID: 77955781184     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2010.5509209     Document Type: Conference Paper

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