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International Conference on Interactive Collaborative Robotics

ICR 2021: Interactive Collaborative Robotics pp 27–39Cite as

Semantic Segmentation in the Task of Long-Term Visual Localization

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12998))

Abstract

In this paper, it is discussed the problem of long-term visual localization with a using of the Aachen Day-Night dataset. Our experiments confirmed that carefully fine-tuning parameters of the Hierarchical Localization method can lead to enhance the visual localization accuracy. Next, our experiments show that it is possible to find an image’s area that does not add any valuable information in long-term visual localization and can be removed without losing the localization accuracy. The approach of using the method of semantic segmentation for preprocessing helped to achieve comparable state-of-the-art results in the Aachen Day-Night dataset.

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Notes

  1. 1.

    https://colmap.github.io/.

  2. 2.

    https://sites.google.com/view/ltvl2020/challenges.

  3. 3.

    https://www.visuallocalization.net.

  4. 4.

    http://www.robustvision.net/rvc2018.php.

  5. 5.

    http://www.robustvision.net.

  6. 6.

    https://www.visuallocalization.net/workshop/eccv/2020/.

  7. 7.

    https://github.com/cvg/Hierarchical-Localization.

  8. 8.

    https://colmap.github.io/.

  9. 9.

    For example, car, bus, and truck classes have vehicles (the group of classes) as high-level interpretations.

  10. 10.

    https://paperswithcode.com/sota/semantic-segmentation-on-cityscapes.

  11. 11.

    https://www.cityscapes-dataset.com.

  12. 12.

    https://github.com/NVIDIA/semantic-segmentation.

  13. 13.

    https://www.visuallocalization.net/benchmark/.

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Acknowledgements

This publication was supported by the project LO1506 of the Czech Ministry of Education, Youth and Sports.

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Authors and Affiliations

  1. Faculty of Applied Sciences, New Technologies for the Information Society, University of West Bohemia, Univerzitní 8, 306 14, Plzeň, Czech Republic

    Lukáš Bureš & Luděk Müller

Authors
  1. Lukáš Bureš
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  2. Luděk Müller
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Correspondence to Lukáš Bureš .

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Editors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Andrey Ronzhin

  2. Technical University of Munich, Munich, Germany

    Gerhard Rigoll

  3. V. A. Trapeznikov Institute of Control Sciences, Moscow, Russia

    Roman Meshcheryakov

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Bureš, L., Müller, L. (2021). Semantic Segmentation in the Task of Long-Term Visual Localization. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2021. Lecture Notes in Computer Science(), vol 12998. Springer, Cham. https://doi.org/10.1007/978-3-030-87725-5_3

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  • DOI: https://doi.org/10.1007/978-3-030-87725-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87724-8

  • Online ISBN: 978-3-030-87725-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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