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Body Posture Estimation in Sign Language Videos

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Gesture in Embodied Communication and Human-Computer Interaction (GW 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5934))

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Abstract

This article deals with the posture reconstruction from a mono view video of a signed utterance. Our method makes no use of additional sensors or visual markers. The head and the two hands are tracked by means of a particle filter. The elbows are detected as convolution local maxima. A non linear filter is first used to remove the outliers, then some criteria using French Sign Language phonology are used to process the hand disambiguation. The posture reconstruction is achieved by using inverse kinematics, using a Kalman smoothing and the correlation between strong and week hand depth that can be noticed in the signed utterances. The article ends with a quantitative and qualitative evaluation of the reconstruction. We show how the results could be used in the framework of automatic Sign Language video processing.

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Author information

Authors and Affiliations

  1. IRIT : UPS-118 r. de Narbonne, 31062, Toulouse cedex 9

    François Lefebvre-Albaret & Patrice Dalle

Authors
  1. François Lefebvre-Albaret
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  2. Patrice Dalle
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Editor information

Editors and Affiliations

  1. CITEC, Bielefeld University, P.O. Box 100131, 33501, Bielefeld, Germany

    Stefan Kopp

  2. Artificial Intelligence Group, Faculty of Technology, Bielefeld University, 33594, Bielefeld, Germany

    Ipke Wachsmuth

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Lefebvre-Albaret, F., Dalle, P. (2010). Body Posture Estimation in Sign Language Videos. In: Kopp, S., Wachsmuth, I. (eds) Gesture in Embodied Communication and Human-Computer Interaction. GW 2009. Lecture Notes in Computer Science(), vol 5934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12553-9_26

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  • DOI: https://doi.org/10.1007/978-3-642-12553-9_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12552-2

  • Online ISBN: 978-3-642-12553-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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