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Asian Conference on Computer Vision

ACCV 2014: Computer Vision -- ACCV 2014 pp 407–423Cite as

On the Performance of Pose-Based RGB-D Visual Navigation Systems

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9004))

Abstract

This paper presents a thorough performance analysis of several variants of the feature-based visual navigation system that uses RGB-D data to estimate in real-time the trajectory of a freely moving sensor. The evaluation focuses on the advantages and problems that are associated with choosing a particular structure of the sensor-tracking front-end, employing particular feature detectors/descriptors, and optimizing the resulting trajectory treated as a graph of sensor poses. Moreover, a novel yet simple graph pruning algorithm is introduced, which enables to remove spurious edges from the pose-graph. The experimental evaluation is performed on two publicly available RGB-D data sets to ensure that our results are scientifically verifiable.

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Acknowledgement

This research was financed by the Polish National Science Centre grant funded according to the decision DEC-2013/09/B/ST7/01583.

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Authors and Affiliations

  1. Institute of Control and Information Engineering, Poznań University of Technology, ul. Piotrowo 3A, 60-965, Poznań, Poland

    Dominik Belter, Michał Nowicki & Piotr Skrzypczyński

Authors
  1. Dominik Belter
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  2. Michał Nowicki
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  3. Piotr Skrzypczyński
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Corresponding author

Correspondence to Piotr Skrzypczyński .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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Belter, D., Nowicki, M., Skrzypczyński, P. (2015). On the Performance of Pose-Based RGB-D Visual Navigation Systems. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9004. Springer, Cham. https://doi.org/10.1007/978-3-319-16808-1_28

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  • DOI: https://doi.org/10.1007/978-3-319-16808-1_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16807-4

  • Online ISBN: 978-3-319-16808-1

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