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Hands Tracking from Frontal View for Vision-Based Gesture Recognition

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Pattern Recognition (DAGM 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2449))

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Abstract

We present a system for tracking the hands of a user in a frontal camera view for gesture recognition purposes. The system uses multiple cues, incorporates tracing and prediction algorithms, and applies probabilistic inference to determine the trajectories of the hands reliably even in case of hand-face overlap. A method for assessing tracking quality is also introduced. Tests were performed with image sequences of 152 signs from German Sign Language, which have been segmented manually beforehand to offer a basis for quantitative evaluation. A hit rate of 81.1% was achieved on this material.

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Author information

Authors and Affiliations

  1. Chair of Technical Computer Science, Aachen University (RWTH), Ahornst. 55, 52074, Aachen, Germany

    Jörg Zieren, Nils Unger & Suat Akyol

Authors
  1. Jörg Zieren
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  2. Nils Unger
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  3. Suat Akyol
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Editor information

Editors and Affiliations

  1. Computer Vision Laboratory, ETH Zürich, Gloriastrasse 35, 8092, Zürich, Switzerland

    Luc Van Gool

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© 2002 Springer-Verlag Berlin Heidelberg

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Zieren, J., Unger, N., Akyol, S. (2002). Hands Tracking from Frontal View for Vision-Based Gesture Recognition. In: Van Gool, L. (eds) Pattern Recognition. DAGM 2002. Lecture Notes in Computer Science, vol 2449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45783-6_64

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  • DOI: https://doi.org/10.1007/3-540-45783-6_64

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44209-7

  • Online ISBN: 978-3-540-45783-1

  • eBook Packages: Springer Book Archive

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