Beyond the Euclidean distance: Creating effective visual codebooks using the histogram intersection kernel

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 630-637

  Wu, Jianxin ^a   Rehg, James M ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAG-OF-VISUAL-WORDS; BENCHMARK DATASETS; CLUSTER FEATURE; CODE-WORDS; CODEBOOK GENERATION; CODEBOOKS; DESCRIPTORS; EUCLIDEAN DISTANCE; GAUSSIAN MIXTURE MODEL; HISTOGRAM FEATURES; HISTOGRAM INTERSECTION; IMAGE MEASUREMENTS; K-MEANS; K-MEDIAN CLUSTERING; KERNEL K-MEANS; ONE CLASS-SVM; RECOGNITION ACCURACY; SCENE RECOGNITION; STATE-OF-THE-ART PERFORMANCE;

COMPUTER VISION; CONTENT BASED RETRIEVAL; FACE RECOGNITION; STATISTICAL METHODS;

GRAPHIC METHODS;

EID: 77953226691     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459178     Document Type: Conference Paper

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