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A Comparison of Directional Distances for Hand Pose Estimation

  • Conference paper
Pattern Recognition (GCPR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8142))

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Abstract

Benchmarking methods for 3d hand tracking is still an open problem due to the difficulty of acquiring ground truth data. We introduce a new dataset and benchmarking protocol that is insensitive to the accumulative error of other protocols. To this end, we create testing frame pairs of increasing difficulty and measure the pose estimation error separately for each of them. This approach gives new insights and allows to accurately study the performance of each feature or method without employing a full tracking pipeline. Following this protocol, we evaluate various directional distances in the context of silhouette-based 3d hand tracking, expressed as special cases of a generalized Chamfer distance form. An appropriate parameter setup is proposed for each of them, and a comparative study reveals the best performing method in this context.

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Author information

Authors and Affiliations

  1. Perceiving Systems Department, MPI for Intelligent Systems, Germany

    Dimitrios Tzionas

  2. Computer Vision Group, University of Bonn, Germany

    Dimitrios Tzionas & Juergen Gall

Authors
  1. Dimitrios Tzionas
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  2. Juergen Gall
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Editor information

Editors and Affiliations

  1. Faculty of Mathematics and Computer Science, Saarland University, Campus E1.7, 66041, Saarbrücken, Germany

    Joachim Weickert

  2. Faculty of Mathematics and Computer Science, Saarland University, Campus E1.3, 66041, Saarbrücken, Germany

    Matthias Hein

  3. Computer Vision and Multimodal Computing, Max-Planck-Institute for Informatics, Campus E 1.4, 66123, Saarbrücken, Germany

    Bernt Schiele

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Tzionas, D., Gall, J. (2013). A Comparison of Directional Distances for Hand Pose Estimation. In: Weickert, J., Hein, M., Schiele, B. (eds) Pattern Recognition. GCPR 2013. Lecture Notes in Computer Science, vol 8142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40602-7_14

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  • DOI: https://doi.org/10.1007/978-3-642-40602-7_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40601-0

  • Online ISBN: 978-3-642-40602-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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