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ICASSP
2008
IEEE

Query adaptative locality sensitive hashing

13 years 10 months ago
Query adaptative locality sensitive hashing
It is well known that high-dimensional nearest-neighbor retrieval is very expensive. Many signal processing methods suffer from this computing cost. Dramatic performance gains can be obtained by using approximate search, such as the popular Locality-Sensitive Hashing. This paper improves LSH by performing an on-line selection of the most appropriate hash functions from a pool of functions. An additional improvement originates from the use of E8 lattices for geometric hashing instead of one-dimensional random projections. A performance study based on state-of-the-art high-dimensional descriptors computed on real images shows that our improvements to LSH greatly reduce the search complexity for a given level of accuracy.
Herve Jegou, Laurent Amsaleg, Cordelia Schmid, Pat
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICASSP
Authors Herve Jegou, Laurent Amsaleg, Cordelia Schmid, Patrick Gros
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