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What Is the Role of Similarity for Known-Item Search at Video Browser Showdown?

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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

Across many domains, machine learning approaches start to compete with human experts in tasks originally considered as very difficult for automation. However, effective retrieval of general video shots still represents an issue due to their variability, complexity and insufficiency of training sets. In addition, users can face problems trying to formulate their search intents in a given query interface. Hence, many systems still rely also on interactive human-machine cooperation to boost effectiveness of the retrieval process. In this paper, we present our experience with known-item search tasks in the Video Browser Showdown competition, where participating interactive video retrieval systems mostly rely on various similarity models. We discuss the observed difficulty of known-item search tasks, categorize employed interaction components (relying on similarity models) and inspect successful interactive known-item searches from the recent iteration of the competition. Finally, open similarity search challenges for known-item search in video are presented.

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Notes

  1. 1.

    www.videobrowsershowdown.org.

  2. 2.

    The tasks at VBS 2018 were organized into three sessions – expert users (ID 1–12), novice users (ID 13–20) and a test session for the experts organized one day before the competition (ID 21–30).

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Acknowledgments

This paper has been supported by Czech Science Foundation (GAČR) project no. 17-22224S and by grant SVV-260451. This work is also supported by Universität Klagenfurt and Lakeside Labs GmbH, Klagenfurt, Austria and funding from the European Regional Development Fund and the Carinthian Economic Promotion Fund (KWF) under grant KWF 20214 u. 3520/26336/38165.

Author information

Authors and Affiliations

  1. Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic

    Jakub Lokoč

  2. DIGITAL–Institute for ICT, JOANNEUM RESEARCH, Graz, Austria

    Werner Bailer

  3. Institute of Information Technology, Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria

    Klaus Schöffmann

Authors
  1. Jakub Lokoč
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  2. Werner Bailer
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  3. Klaus Schöffmann
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Corresponding author

Correspondence to Werner Bailer .

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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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Lokoč, J., Bailer, W., Schöffmann, K. (2018). What Is the Role of Similarity for Known-Item Search at Video Browser Showdown?. 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_8

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  • DOI: https://doi.org/10.1007/978-3-030-02224-2_8

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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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