Sufficient dimension reduction for visual sequence classification

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

Volumn , Issue , 2010, Pages 3610-3617

  Shyr, Alex ^a   Urtasun, Raquel ^b   Jordan, Michael I ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DEGREES OF FREEDOM; DIMENSIONALITY REDUCTION; DYNAMIC TEXTURES; EXISTING METHOD; HIGH-DIMENSIONAL; HUMAN GESTURES; INPUT DATAS; KERNEL DIMENSION; LOW-DIMENSIONAL REPRESENTATION; NEIGHBORHOOD GRAPHS; OUTPUT VALUES; OVERFITTING; SEQUENCE CLASSIFICATION; SEQUENCE DATA; SUFFICIENT DIMENSION REDUCTION; TRAINING DATA;

COMPUTER VISION;

DATA REDUCTION;

EID: 77956002956     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5539922     Document Type: Conference Paper

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