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Conference Papers Year : 2012

Anti-sparse coding for approximate nearest neighbor search

Abstract

This paper proposes a binarization scheme for vectors of high dimension based on the recent concept of anti-sparse coding, and shows its excellent performance for approximate nearest neighbor search. Unlike other binarization schemes, this framework allows, up to a scaling factor, the explicit reconstruction from the binary representation of the original vector. The paper also shows that random projections which are used in Locality Sensitive Hashing algorithms, are significantly outperformed by regular frames for both synthetic and real data if the number of bits exceeds the vector dimensionality, i.e., when high precision is required.
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Dates and versions

hal-00661591 , version 1 (20-01-2012)

Identifiers

  • HAL Id : hal-00661591 , version 1

Cite

Hervé Jégou, Teddy Furon, Jean-Jacques Fuchs. Anti-sparse coding for approximate nearest neighbor search. ICASSP - 37th International Conference on Acoustics, Speech, and Signal Processing, Mar 2012, Kyoto, Japan. ⟨hal-00661591⟩
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