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Velocity profile based recognition of dynamic gestures with discrete Hidden Markov Models

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Gesture and Sign Language in Human-Computer Interaction (GW 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1371))

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Abstract

In this paper we present a method for the recognition of dynamic gestures with discrete Hidden Markov Models (HMMs) from a continuous stream of gesture input data. The segmentation problem is addressed by extracting two velocity profiles from the gesture data and using their extrema as segmentation cues. Gestures are captured with a TUB-SensorGlove. The paper focuses on the description of the gesture recognition method (including data preprocessing) and describes experiments for the evaluation of the performance of the recognition method. The paper combines and further develops ideas from some of our previous work.

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Authors and Affiliations

  1. Department of Computer Science, Technical University of Berlin, FR2-2, Franklinstr. 28/29, D-10587, Berlin, Germany

    Frank G. Hofmann, Peter Heyer & Günter Hommel

Authors
  1. Frank G. Hofmann
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  2. Peter Heyer
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  3. Günter Hommel
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Editor information

Ipke Wachsmuth Martin Fröhlich

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© 1998 Springer-Verlag

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Hofmann, F.G., Heyer, P., Hommel, G. (1998). Velocity profile based recognition of dynamic gestures with discrete Hidden Markov Models. In: Wachsmuth, I., Fröhlich, M. (eds) Gesture and Sign Language in Human-Computer Interaction. GW 1997. Lecture Notes in Computer Science, vol 1371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052991

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  • DOI: https://doi.org/10.1007/BFb0052991

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64424-8

  • Online ISBN: 978-3-540-69782-4

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