Efficient multi-step query processing for EMD-based similarity

Authors Ira Assent, Thomas Seidl



PDF
Thumbnail PDF

File

DagSemProc.06171.6.pdf
  • Filesize: 264 kB
  • 12 pages

Document Identifiers

Author Details

Ira Assent
Thomas Seidl

Cite AsGet BibTex

Ira Assent and Thomas Seidl. Efficient multi-step query processing for EMD-based similarity. In Content-Based Retrieval. Dagstuhl Seminar Proceedings, Volume 6171, pp. 1-12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)
https://doi.org/10.4230/DagSemProc.06171.6

Abstract

Similarity search in large multimedia databases requires ef- ficient query processing based on suitable similarity models. Similarity models consist of a feature extraction step as well as a distance defined for these features, and they demand an efficient algorithm for retrieving similar objects under this model. In this work, we focus on the Earth Movers Distance (EMD), a recently introduced similarity model which has been successfully employed in numerous applications and has been reported as well reflecting human perceptual similarity. As its computation is complex, the direct application of the EMD to large, high-dimensional databases is not feasible. To remedy this and allow users to benefit from the high quality of the model even in larger settings, we developed various lower bounds for the EMD to be used in index-supported multistep query processing algorithms. We prove that our algorithms are complete, thus producing no false drops. We also show that it is highly efficient as experiments on large image databases with high-dimensional features demonstrate.
Keywords
  • Content-based retrieval
  • indexing
  • multimedia databases
  • efficiency
  • similarity

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail