Model-based similarity estimation of multidimensional temporal sequences

  • Romain Tavenard
  • Laurent Amsaleg
  • Guillaume Gravier
Article

Abstract

Content-based queries in multimedia sequence databases where information is sequential is a tough issue, especially when dealing with large-scale applications. One of the key points is similarity estimation between a query sequence and elements of the database. In this paper, we investigate two ways to compare multimedia sequences, one—that comes from the literature—being computed in the feature space while the other one is computed in a model space, leading to a representation less sensitive to noise. We compare these approaches by testing them on a real audio dataset, which points out the utility of working in the model space.

Keywords

Multidimensional feature sequences Support vector regression Temporal aspects Similarity estimation in a model space 

Copyright information

© Institut TELECOM and Springer-Verlag 2009

Authors and Affiliations

  • Romain Tavenard
    • 1
  • Laurent Amsaleg
    • 2
  • Guillaume Gravier
    • 2
  1. 1.IRISA / ENS CachanRennes CedexFrance
  2. 2.CNRS / IRISARennes CedexFrance

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