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Handbook of Human Motion pp 2003–2031Cite as

Data-Driven Character Animation Synthesis

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Abstract

In this article, we describe about data-driven character motion synthesis for use mainly on a full-body skeleton structure. Due to the simplicity of capturing motion nowadays, the main issue for animating characters is how to reduce the cost of applying such motion to the characters and how to recycle the motion for interactive motion synthesis. An additional topic of interest is how to convert the style of the movements while preserving the context of the motion. In this article, we primarily cover machine learning techniques that can be useful for such purposes.

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Authors and Affiliations

  1. School of Informatics, University of Edinburgh, Edinburgh, UK

    Taku Komura, Ikhsanul Habibie, Jonathan Schwarz & Daniel Holden

Authors
  1. Taku Komura
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  2. Ikhsanul Habibie
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  3. Jonathan Schwarz
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  4. Daniel Holden
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Corresponding author

Correspondence to Taku Komura .

Section Editor information

  1. Institut for Biomechanics und Orthopedic, German Sport University Cologne, Cologne, Germany

    Gert-Peter Brüggemann

  2. Department of Computer Science, University of Houston, Houston, Texas, USA

    Zhigang Deng

  3. McIntosh Consultancy and Research, Sydney, New South Wales, Australia

    Andrew S. McIntosh

  4. Wilmington, Delaware, USA

    Freeman Miller

  5. C-Motion Inc., Germantown, USA

    W. Scott Selbie

  6. Department of Computer Science,, University of Houston, Houston, TX, USA

    Zhigang Deng

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Komura, T., Habibie, I., Schwarz, J., Holden, D. (2018). Data-Driven Character Animation Synthesis. In: Handbook of Human Motion. Springer, Cham. https://doi.org/10.1007/978-3-319-14418-4_10

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