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Selective and Simple Graph Structures for Better Description of Local Point-Based Image Features

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Computer Vision and Graphics (ICCVG 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11114))

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Abstract

The paper presents simple graph features based on a well-known image keypoints. We discuss the extraction method and geometrical properties that can be used. Chosen methods are tested in KNN tasks for almost 1000 object classes. The approach addresses problems in applications that cannot use learning methods explicitly, as real-time tracking, chosen object detection scenarios and structure from motion. Results imply that the idea is worth further research for chosen systems.

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Author information

Authors and Affiliations

  1. Institute of Control and Industrial Electronics, Warsaw University of Technology, ul.Koszykowa 75, 00-662, Warsaw, Poland

    Grzegorz Kurzejamski & Marcin Iwanowski

Authors
  1. Grzegorz Kurzejamski
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  2. Marcin Iwanowski
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Corresponding author

Correspondence to Grzegorz Kurzejamski .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences, Warsaw, Poland

    Leszek J. Chmielewski

  2. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences, Warsaw, Poland

    Ryszard Kozera

  3. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences, Warsaw, Poland

    Arkadiusz Orłowski

  4. Institute of Computer Science, Silesian University of Technology, Gliwice, Poland

    Konrad Wojciechowski

  5. Technion, Israel Institute of Technology, Haifa, Israel

    Alfred M. Bruckstein

  6. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

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Kurzejamski, G., Iwanowski, M. (2018). Selective and Simple Graph Structures for Better Description of Local Point-Based Image Features. In: Chmielewski, L., Kozera, R., Orłowski, A., Wojciechowski, K., Bruckstein, A., Petkov, N. (eds) Computer Vision and Graphics. ICCVG 2018. Lecture Notes in Computer Science(), vol 11114. Springer, Cham. https://doi.org/10.1007/978-3-030-00692-1_12

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  • DOI: https://doi.org/10.1007/978-3-030-00692-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00691-4

  • Online ISBN: 978-3-030-00692-1

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