Interactive-Time Similarity Search for Large Image Collections Using Parallel VA-Files

  • Roger Weber
  • Klemens Böhm
  • Hans-J. Schek
Conference paper

DOI: 10.1007/3-540-45268-0_8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1923)
Cite this paper as:
Weber R., Böhm K., Schek HJ. (2000) Interactive-Time Similarity Search for Large Image Collections Using Parallel VA-Files. In: Borbinha J., Baker T. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2000. Lecture Notes in Computer Science, vol 1923. Springer, Berlin, Heidelberg

Abstract

In digital libraries, nearest-neighbor search (NN-search) plays a key role for content-based retrieval over multimedia objects. However, performance of existing NN-search techniques is not satisfactory with large collections and with high-dimensional representations of the objects. To obtain response times that are interactive, we pursue the following approach: it uses a linear algorithm that works with approximations of the vectors and parallelizes it. In more detail, we parallelize NN-search based on the VA-File in a Network of Workstations (NOW). This approach reduces search time to a reasonable level for large collections. The best speedup we have observed is by almost 30 for a NOW with only three components with 900 MB of feature data. But this requires a number of design decisions, in particular when taking load dynamism and heterogeneity of components into account. Our contribution is to address these design issues.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Roger Weber
    • 1
  • Klemens Böhm
    • 1
  • Hans-J. Schek
    • 1
  1. 1.Institute of Information SystemsETH ZentrumZurichSwitzerland

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