DocumentCode :
3647702
Title :
Fast computation of min-Hash signatures for image collections
Author :
Ondřej Chum;Jiří Matas
Author_Institution :
Centre for Machine Perception Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
3077
Lastpage :
3084
Abstract :
A new method for highly efficient min-Hash generation for document collections is proposed. It exploits the inverted file structure which is available in many applications based on a bag or a set of words. Fast min-Hash generation is important in applications such as image clustering where good recall and precision requires a large number of min-Hash signatures. Using the set of words represenation, the novel exact min-Hash generation algorithm achieves approximately a 50-fold speed-up on two dataset with 105 and 106 images respectively. We also propose an approximate min-Hash assignment process which reaches a more than 200-fold speed-up at the cost of missing about 2-3% of matches. We also experimentally show that the method generalizes to other modalities with significantly different statistics.
Keywords :
"Visualization","Vocabulary","Standards","Image resolution","Complexity theory","Algorithm design and analysis","Equations"
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
ISSN :
1063-6919
Print_ISBN :
978-1-4673-1226-4
Type :
conf
DOI :
10.1109/CVPR.2012.6248039
Filename :
6248039
Link To Document :
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