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Automating Expressive Locomotion Generation

  • Conference paper
Transactions on Edutainment VII

Part of the book series: Lecture Notes in Computer Science ((TEDUTAIN,volume 7145))

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Abstract

This paper introduces a system for expressive locomotion generation that takes as input a set of sample locomotion clips and a motion path. Significantly, the system only requires a single sample of straight-path locomotion for each style modeled and can produce output locomotion for an arbitrary path with arbitrary motion transition points. For efficient locomotion generation, we represent each sample with a loop sequence which encapsulates its key style and utilize these sequences throughout the synthesis process. Several techniques are applied to automate the synthesis: foot-plant detection from unlabeled samples, estimation of an adaptive blending length for a natural style change, and a post-processing step for enhancing the physical realism of the output animation. Compared to previous approaches, the system requires significantly less data and manual labor, while supporting a large range of styles.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Program for Technocultural Studies, University of California, 1 Shields Avenue, Davis, CA, 95616, U.S.A.

    Yejin Kim & Michael Neff

Authors
  1. Yejin Kim
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  2. Michael Neff
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Editor information

Editors and Affiliations

  1. Hangzhou Normal University, Hangzhou, China

    Zhigeng Pan

  2. National University of Singapore, Singapore

    Adrian David Cheok

  3. University of Education, Weingarten, Germany

    Wolfgang Müller

  4. Athabasca University, AB, Canada

    Maiga Chang

  5. Zhejiang University, Hangzhou, China

    Mingmin Zhang

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© 2012 Springer-Verlag Berlin Heidelberg

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Kim, Y., Neff, M. (2012). Automating Expressive Locomotion Generation. In: Pan, Z., Cheok, A.D., Müller, W., Chang, M., Zhang, M. (eds) Transactions on Edutainment VII. Lecture Notes in Computer Science, vol 7145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29050-3_5

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  • DOI: https://doi.org/10.1007/978-3-642-29050-3_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29049-7

  • Online ISBN: 978-3-642-29050-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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