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Retrieving Emotion from Motion Analysis: In a Real Time Parallel Framework for Robots

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Neural Information Processing (ICONIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5864))

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Abstract

This paper presents a parallel real time framework for emotion extraction from video fragments of human movements. Its framework is used for tracking of a waving hand by evaluation of moving skin-colored objects. The tracking analysis demonstrates that acceleration and frequency characteristics of the traced objects are relevant for classification of the emotional expressiveness of human movements. The solution is part of a larger project on interaction between a human and a humanoid robot with the aim of training social behavioral skills to autistic children with robots acting in a natural environment.

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Authors and Affiliations

  1. Eindhoven University of Technology, P.O. Box 513, Eindhoven, The Netherlands

    Tino Lourens & Emilia Barakova

Authors
  1. Tino Lourens
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  2. Emilia Barakova
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, City University of Hong Kong, Hong Kong,  

    Chi Sing Leung

  2. School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  3. School of Information Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-U-Thit Rd., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Jonathan H. Chan

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© 2009 Springer-Verlag Berlin Heidelberg

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Lourens, T., Barakova, E. (2009). Retrieving Emotion from Motion Analysis: In a Real Time Parallel Framework for Robots. In: Leung, C.S., Lee, M., Chan, J.H. (eds) Neural Information Processing. ICONIP 2009. Lecture Notes in Computer Science, vol 5864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10684-2_48

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  • DOI: https://doi.org/10.1007/978-3-642-10684-2_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10682-8

  • Online ISBN: 978-3-642-10684-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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