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Extended Keypoint Description and the Corresponding Improvements in Image Retrieval

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Computer Vision - ACCV 2014 Workshops (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9008))

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Abstract

The paper evaluates an alternative approach to BoW-based image retrieval in large databases. The major improvements are in the re-ranking step (verification of candidates returned by BoW). We propose a novel keypoint description which allows the verification based only on individual keypoint matching (no spatial consistency over groups of matched keypoints is tested). Standard Harris-Affine and Hessian-Affine keypoint detectors with SIFT descriptor are used. The proposed description assigns to each keypoint several words representing photometry and geometry of the keypoint in the context of neighbouring image fragments. The words are Cartesian products of typical SIFT-based words so that huge vocabularies can be built. The preliminary experiments on several popular datasets show significant improvements in the pre-retrieval phase combined with a dramatically lower complexity of the re-ranking process. Because of that, the proposed methodology is particularly recommended for the retrieval in very large datasets.

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Notes

  1. 1.

    http://www.robots.ox.ac.uk/~vgg/research/affine/.

  2. 2.

    http://www.robots.ox.ac.uk/~vgg/data/oxbuildings/.

  3. 3.

    http://www.vis.uky.edu/~stewe/ukbench/.

  4. 4.

    http://156.17.10.3/~visible/data/upload/FragmentMatchingDB.zip.

  5. 5.

    http://www.vision.caltech.edu/html-files/archive.html.

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Author information

Authors and Affiliations

  1. Khalifa University, Abu Dhabi, United Arab Emirates

    Andrzej Śluzek

Authors
  1. Andrzej Śluzek
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Correspondence to Andrzej Śluzek .

Editor information

Editors and Affiliations

  1. Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India

    C.V. Jawahar

  2. Institue of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

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Śluzek, A. (2015). Extended Keypoint Description and the Corresponding Improvements in Image Retrieval. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9008. Springer, Cham. https://doi.org/10.1007/978-3-319-16628-5_50

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  • DOI: https://doi.org/10.1007/978-3-319-16628-5_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16627-8

  • Online ISBN: 978-3-319-16628-5

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