Walk This Way: A Lightweight, Data-Driven Walking Synthesis Algorithm

  • Sean Curtis
  • Ming Lin
  • Dinesh Manocha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7060)

Abstract

We present a novel, biomechanically-inspired, kinematic- based, example-driven walking synthesis model. Our model is ideally suited towards interactive applications such as games. It synthesizes motion interactively without a priori knowledge of the trajectory. The model is very efficient, producing foot-skate free, smooth motion over a large, continuous range of speeds and while turning, in as little as 5 μs. We’ve formulated our model so that an artist has extensive control over how the walking gait manifests itself at all speeds.

Keywords

Initial Contact Stride Length Stride Frequency Warp Function Gait Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sean Curtis
    • 1
  • Ming Lin
    • 1
  • Dinesh Manocha
    • 1
  1. 1.University of North Carolina at Chapel HillChapel HillUSA

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