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International Conference on Articulated Motion and Deformable Objects

AMDO 2010: Articulated Motion and Deformable Objects pp 98–107Cite as

Learning Generic Human Body Models

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6169))

Abstract

We describe a posture estimation system based on Organic Computing concepts, which learns a generic body model from video input in a self-governed manner. We show experimentally that the constructed model generalizes well to different attire and persons.

Funding by the DFG (WU 314/5-2, WU 314/5-3) is gratefully acknowledged.

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Author information

Authors and Affiliations

  1. Institut für Neuroinformatik, Ruhr-Universität, 44780, Bochum, Germany

    Thomas Walther & Rolf P. Würtz

Authors
  1. Thomas Walther
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  2. Rolf P. Würtz
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Editors and Affiliations

  1. Unitat de Gràfics i Visió per Ordinador Departament de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears Edifici Anselm Turmeda, Ctra. de Valldemossa km 7,5, 07122, Palma de Mallorca, Spain

    Francisco J. Perales

  2. School of Informatics, University of Edinburgh, James Clerk Maxwell Building, The King’s Buildings, Mayfield Road, EH9 3JZ, Edinburgh, UK

    Robert B. Fisher

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Walther, T., Würtz, R.P. (2010). Learning Generic Human Body Models. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2010. Lecture Notes in Computer Science, vol 6169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14061-7_10

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  • DOI: https://doi.org/10.1007/978-3-642-14061-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14060-0

  • Online ISBN: 978-3-642-14061-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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