DocumentCode :
3413227
Title :
Permutation grouping: intelligent Hash function design for audio & image retrieval
Author :
Baluja, Sanjeev ; Covell, Michele ; Ioffe, Sergey
Author_Institution :
Google Res., Google Inc., Mountain View, CA
fYear :
2008
fDate :
March 31 2008-April 4 2008
Firstpage :
2137
Lastpage :
2140
Abstract :
The combination of MinHash-based signatures and locality- sensitive hashing (LSH) schemes has been effectively used for finding approximate matches in very large audio and image retrieval systems. In this study, we introduce the idea of permutation-grouping to intelligently design the hash functions that are used to index the LSH tables. This helps to overcome the inefficiencies introduced by hashing real-world data that is noisy, structured, and most importantly is not independently and identically distributed. Through extensive tests, we find that permutation-grouping dramatically increases the efficiency of the overall retrieval system by lowering the number of low-probability candidates that must be examined by 30-50%.
Keywords :
audio signal processing; cryptography; database indexing; digital signatures; image retrieval; very large databases; LSH schemes; LSH table indexing; MinHash-based signatures; intelligent hash function design; large databases; locality-sensitive hashing; permutation grouping; very large audio retrieval systems; very large image retrieval systems; Image retrieval; Audio Retrieval; Image Retrieval; LSH; MinHash;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
ISSN :
1520-6149
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2008.4518065
Filename :
4518065
Link To Document :
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