DocumentCode
3281352
Title
Multi-criteria search algorithm: An efficient approximate k-NN algorithm for image retrieval
Author
Badr, Mario ; Vodislav, Dan ; Picard, David ; Shaoyi Yin ; Gosselin, Philippe-Henri
Author_Institution
ENSEA, ETIS Univ. of Cergy-Pontoise, Cergy-Pontoise, France
fYear
2013
fDate
15-18 Sept. 2013
Firstpage
2901
Lastpage
2905
Abstract
We propose a new method for approximate k-NN search in large scale image databases, based on top-k multi-criteria search techniques. The method defines a simple index structure based on sorted lists, which provides a good compromise between fast retrieval, storage requirements and update cost. The search algorithm delivers approximate results with guarantees about false negatives, with fast emergence of good approximations, monotonically improved and leading if necessary to an exact result. Experiments with the on-disk implementation show that our method produces very good approximate results several times faster than the Baseline method.
Keywords
content-based retrieval; image retrieval; learning (artificial intelligence); search problems; sorting; visual databases; approximate k-NN search algorithm; baseline method; false negatives; fast retrieval; index structure; k nearest neighbors; large scale content based image retrieval; large scale image databases; multicriteria search algorithm; sorted lists; storage requirements; top-k multicriteria search techniques; update cost; CBIR; image databases; k-NN search; multi-criteria search; top-k algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location
Melbourne, VIC
Type
conf
DOI
10.1109/ICIP.2013.6738597
Filename
6738597
Link To Document