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Transactional Support for Visual Instance Search

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Similarity Search and Applications (SISAP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11223))

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Abstract

This article addresses the issue of dynamicity and durability for scalable indexing of very large and rapidly growing collections of local features for visual instance retrieval. By extending the NV-tree, a scalable disk-based high-dimensional index, we show how to implement the ACID properties of transactions which ensure both dynamicity and durability. We present a detailed performance evaluation of the transactional NV-tree, showing that the insertion throughput is excellent despite the effort to enforce the ACID properties.

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Author information

Authors and Affiliations

  1. Videntifier Technologies, Reykjavik, Iceland

    Herwig Lejsek & Friðrik Heiðar Ásmundsson

  2. Reykjavík University, Reykjavik, Iceland

    Björn Þór Jónsson

  3. IT University of Copenhagen, Copenhagen, Denmark

    Björn Þór Jónsson

  4. CNRS–IRISA, Rennes, France

    Laurent Amsaleg

Authors
  1. Herwig Lejsek
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  2. Friðrik Heiðar Ásmundsson
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  3. Björn Þór Jónsson
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  4. Laurent Amsaleg
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Corresponding author

Correspondence to Laurent Amsaleg .

Editor information

Editors and Affiliations

  1. University of Geneva, Carouge, Switzerland

    Stéphane Marchand-Maillet

  2. Arizona State University, Tempe, AZ, USA

    Yasin N. Silva

  3. Center for Scientific Research and Higher Education, Ensenada, Mexico

    Edgar Chávez

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Lejsek, H., Ásmundsson, F.H., Jónsson, B.Þ., Amsaleg, L. (2018). Transactional Support for Visual Instance Search. In: Marchand-Maillet, S., Silva, Y., Chávez, E. (eds) Similarity Search and Applications. SISAP 2018. Lecture Notes in Computer Science(), vol 11223. Springer, Cham. https://doi.org/10.1007/978-3-030-02224-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-02224-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02223-5

  • Online ISBN: 978-3-030-02224-2

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