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Fast Techniques for Monocular Visual Odometry

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Pattern Recognition (DAGM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9358))

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Abstract

In this paper, fast techniques are proposed to achieve real time and robust monocular visual odometry. We apply an iterative 5-point method to estimate instantaneous camera motion parameters in the context of a RANSAC algorithm to cope with outliers efficiently. In our method, landmarks are localized in space using a probabilistic triangulation method utilized to enhance the estimation of the last camera pose. The enhancement is performed by multiple observations of landmarks and minimization of a cost function consisting of epipolar geometry constraints for far landmarks and projective constraints for close landmarks. The performance of the proposed method is demonstrated through application to the challenging KITTI visual odometry dataset.

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Author information

Authors and Affiliations

  1. GET Lab, University of Paderborn, Pohlwegstr 47-49, 33098, Paderborn, Germany

    M. Hossein Mirabdollah & Bärbel Mertsching

Authors
  1. M. Hossein Mirabdollah
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  2. Bärbel Mertsching
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Corresponding author

Correspondence to M. Hossein Mirabdollah .

Editor information

Editors and Affiliations

  1. Institute of Computer Science III, University of Bonn, Bonn, Germany

    Juergen Gall

  2. MPI for Intelligent Systems, University of TĂĽbingen, TĂĽbingen, Germany

    Peter Gehler

  3. Computer Vision Group, Visual Computing Institute, RWTH Aachen, Aachen, Germany

    Bastian Leibe

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Mirabdollah, M.H., Mertsching, B. (2015). Fast Techniques for Monocular Visual Odometry. In: Gall, J., Gehler, P., Leibe, B. (eds) Pattern Recognition. DAGM 2015. Lecture Notes in Computer Science(), vol 9358. Springer, Cham. https://doi.org/10.1007/978-3-319-24947-6_24

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  • DOI: https://doi.org/10.1007/978-3-319-24947-6_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24946-9

  • Online ISBN: 978-3-319-24947-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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