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Recognition of gestures in the context of speech
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0002-5750-9655
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
2002 (English)In: 16th International Conference on Pattern Recognition, 2002. Proceedings., 2002Conference paper, Published paper (Refereed)
Abstract [en]

The scope of this paper is the interpretation of a user's intention via a video camera and a speech recognizer In comparison to previous work which only takes into account gesture recognition, we demonstrate that by including speech, system comprehension increases. For the gesture recognition, the user must wear a colored glove, then we extract the velocity of the center of gravity of the hand. A Hidden Markov Model (HMM) is learned for each gesture that we want to recognize. In a dynamic action, to know if a gesture has been performed or not, we implement a threshold model below which the gesture is not detected. The off line tests for gesture recognition have a success rate exceeding 85% for each gesture. The combination of speech and gestures is realized using Bayesian theory.

Place, publisher, year, edition, pages
2002.
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-49465DOI: 10.1109/ICPR.2002.1044723OAI: oai:DiVA.org:kth-49465DiVA: diva2:459711
Conference
IAPR International Conference on Pattern Recognition.
Note
QC 20111201Available from: 2011-11-28 Created: 2011-11-28 Last updated: 2011-12-01Bibliographically approved

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Sidenbladh, Hedvig

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  • apa
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  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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  • text
  • asciidoc
  • rtf