Title
Compact projection: Simple and efficient near neighbor search with practical memory requirements
Abstract
Image similarity search is a fundamental problem in computer vision. Efficient similarity search across large image databases depends critically on the availability of compact image representations and good data structures for indexing them. Numerous approaches to the problem of generating and indexing image codes have been presented in the literature, but existing schemes generally lack explicit estimates of the number of bits needed to effectively index a given large image database. We present a very simple algorithm for generating compact binary representations of imagery data, based on random projections. Our analysis gives the first explicit bound on the number of bits needed to effectively solve the indexing problem. When applied to real image search tasks, these theoretical improvements translate into practical performance gains: experimental results show that the new method, while using significantly less memory, is several times faster than existing alternatives.
Year
DOI
Venue
2010
10.1109/CVPR.2010.5539973
CVPR
Keywords
Field
DocType
compact projection,image representation,image similarity search,image coding,image code indexing,visual databases,data structures,data structure,binary representation,image retrieval,practical memory requirement,computer vision,image database,near neighbor search,memory management,indexing,information retrieval,indexation,computer science,approximation algorithms,similarity search
Approximation algorithm,Data structure,Computer vision,Computer science,Image retrieval,Search engine indexing,Theoretical computer science,Memory management,Artificial intelligence,Real image,Nearest neighbor search,Binary number
Conference
Volume
Issue
ISSN
2010
1
1063-6919
ISBN
Citations 
PageRank 
978-1-4244-6984-0
18
0.96
References 
Authors
16
6
Name
Order
Citations
PageRank
Kerui Min11035.33
Linjun Yang2155665.20
John Wright310974361.48
Lei Wu466940.02
Xian-Sheng Hua56566328.17
Yi Ma614931536.21