Snake Table: A Dynamic Pivot Table for Streams of k-NN Searches

  • Juan Manuel Barrios
  • Benjamin Bustos
  • Tomáš Skopal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7404)

Abstract

We present the Snake Table, an index structure designed for supporting streams of k-NN searches within a content-based similarity search framework. The index is created and updated in the online phase while resolving the queries, thus it does not need a preprocessing step. This index is intended to be used when the stream of query objects fits a snake distribution, that is, when the distance between two consecutive query objects is small. In particular, this kind of distribution is present in content-based video retrieval systems, when the set of query objects are consecutive frames from a query video. We show that the Snake Table improves the efficiency of k-NN searches in these systems, avoiding the building of a static index in the offline phase.

Keywords

Similarity Search Metric Indexing Multimedia Information Retrieval Content-Based Video Retrieval 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Juan Manuel Barrios
    • 1
  • Benjamin Bustos
    • 1
  • Tomáš Skopal
    • 2
  1. 1.KDW+PRISMA, Department of Computer ScienceUniversity of ChileChile
  2. 2.SIRET Research Group, Faculty of Mathematics and PhysicsCharles University in PragueCzech Republic

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