Cascade object detection with deformable part models

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

Volumn , Issue , 2010, Pages 2241-2248

  Felzenszwalb, Pedro F ^a   Girshick, Ross B ^a   McAllester, David ^b  

^a UNIVERSITY OF CHICAGO   (United States)

^b TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CASCADE CLASSIFIERS; DEFORMABLE MODELS; DETECTION ACCURACY; DETECTION ALGORITHM; GENERAL CLASS; GENERAL METHOD; GRAMMAR FORMALISMS; HYPOTHESIS PRUNING; OBJECT DETECTION; ORDER OF MAGNITUDE; PICTORIAL STRUCTURES; POSITIVE EXAMPLES; PROBABLY APPROXIMATELY CORRECT LEARNING; SIMPLE ALGORITHM; SMALL SAMPLES; SPEED-UPS; STRUCTURED MODEL;

COMPUTER VISION; DEFORMATION; OBJECT RECOGNITION;

ALGORITHMS;

EID: 77955999401     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5539906     Document Type: Conference Paper

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