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International Workshop on Adaptive Multimedia Retrieval

AMR 2012: Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation pp 102–115Cite as

Optimized SIFT Feature Matching for Image Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8382))

Abstract

Applying SIFT features for retrieval of visual data not only requires proper settings for the descriptor extraction but also needs well selected parameters for comparing these descriptors. Most researchers simply apply the standard values of the parameters without an adequate analysis of the parameters themselves. In this paper, we question the standard parameter settings and investigate the influence of the important comparison parameters. Based on the analysis on diverse data sets using different interest point detectors, we finally present an optimized combination of matching parameters which outperforms the standard values. We observe that two major parameters, i.e., distmax and ratiomax seem to have similar outcomes on different datasets of diverse nature for the application of scene retrieval. Thus, this paper shows that there is an almost global setting for these two parameters for local feature matching. The outcomes of this work can also apply to other tasks like video analysis and object retrieval.

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Acknowledgment

This research was funded by BMBF grant INBEKI \(13N10787\).

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Authors and Affiliations

  1. German Research Center for Artificial Intelligence (DFKI), Trippstadter Str. 122, 67663, Kaiserslautern, Germany

    Christian Schulze & Marcus Liwicki

Authors
  1. Christian Schulze
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  2. Marcus Liwicki
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Corresponding author

Correspondence to Christian Schulze .

Editor information

Editors and Affiliations

  1. Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany

    Andreas Nürnberger

  2. Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany

    Sebastian Stober

  3. Royal School of Library and Information Science, Copenhagen, Denmark

    Birger Larsen

  4. Université Pierre et Marie Curie, Paris, France

    Marcin Detyniecki

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Schulze, C., Liwicki, M. (2014). Optimized SIFT Feature Matching for Image Retrieval. In: Nürnberger, A., Stober, S., Larsen, B., Detyniecki, M. (eds) Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation. AMR 2012. Lecture Notes in Computer Science(), vol 8382. Springer, Cham. https://doi.org/10.1007/978-3-319-12093-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-12093-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12092-8

  • Online ISBN: 978-3-319-12093-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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