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3D pose estimation for articulated vehicles using Kalman-filter based tracking

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Abstract

Knowledge about relative poses within a tractor/trailer combination is a vital prerequisite for kinematic modelling and trajectory estimation. In case of autonomous vehicles or driver assistance systems, for example, the monitoring of an attached passive trailer is crucial for operational safety. We propose a camerabased 3D pose estimation system based on a Kalman-filter. It is evaluated against previously published methods for the same problem.

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Authors and Affiliations

  1. Active Vision Group, Institute for Computational Visualistics, University of Koblenz-Landau, Koblenz, Germany

    C. Fuchs, F. Neuhaus & D. Paulus

Authors
  1. C. Fuchs
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  2. F. Neuhaus
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  3. D. Paulus
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Corresponding author

Correspondence to C. Fuchs.

Additional information

This paper uses the materials of the report submitted at the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding, held on Koblenz, December 1–5, 2014 (OGRW-9-2014).

The article is published in the original.

Christian Fuchs, born 1987, received a Diploma degree in Computer Science from the University of Koblenz-Landau in 2011. He works as a research associate in the active vision group. His primary research interests are 3D pose estimation, stereo vision and driver assistance systems.

Frank Neuhaus, born 1985, received a Diploma degree in Computer Science from the University of Koblenz-Landau where he graduated with honors in 2011. Since then he works as a research associate in the active vision group. His research is focused on 3D mapping, probabilistic modeling and state estimation.

Dietrich Paulus, born 1959, obtained a Bachelor degree in Computer Science from University of Western Ontario, London, Canada, followed by a diploma (Dipl.-Inf.) in Computer Science and a PhD (Dr.Ing.) from Friedrich-Alexander University Erlangen-Nuremberg, Germany. He obtained his habilitation in Erlangen in 2001. Since 2001 he is at the Institute for Computational Visualistics at the University KoblenzLandau, Germany where he became a full professor in 2002. His primary interests are computer vision and robot vision.

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Fuchs, C., Neuhaus, F. & Paulus, D. 3D pose estimation for articulated vehicles using Kalman-filter based tracking. Pattern Recognit. Image Anal. 26, 109–113 (2016). https://doi.org/10.1134/S1054661816010077

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  • DOI: https://doi.org/10.1134/S1054661816010077

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