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A Method to Create Fluttering Hair Animations That Can Reproduce Animator’s Techniques

Published:17 November 2019Publication History

ABSTRACT

We propose a method based on an animator’s technique to create an animation for fluttering objects in the wind such as hair and flag. As a preliminary study, we analyzed how the fluttering objects were expressed in the hand-drawn animations, and confirmed that there is a traditional technique commonly used by professional animators. In the case of hair, for example, the tip of the hair is often moved in the shape of a figure eight, and the remaining hair bundle is animated as if a wave caused by this movement is propagating along the hair. Based on this observation, we developed a system to reproduce this technique digitally. In this system, trajectories of a few control points on a hair bone are sketched by a user, and their motion are propagated to the whole hair bundle to represent the waving behavior. In this process, user can interactively adjust two parameters on swing speed and wave propagation delay. As system evaluation, we conducted a user test in which a sample animation was reproduced by several subjects using our system.

References

  1. Jun Xing, Rubaiat Habib Kazi, Tovi Grossman, Li-Yi Wei, Jos Stam, and George W. Fitzmaurice. 2016. Energy-Brushes: Interactive Tools for Illustrating Stylized Elemental Dynamics. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology, UIST 2016, Tokyo, Japan, October 16-19, 2016. 755–766. https://doi.org/10.1145/2984511.2984585Google ScholarGoogle ScholarDigital LibraryDigital Library

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        • Published in

          cover image ACM Conferences
          SA '19: SIGGRAPH Asia 2019 Posters
          November 2019
          94 pages
          ISBN:9781450369435
          DOI:10.1145/3355056

          Copyright © 2019 Owner/Author

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 17 November 2019

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          Overall Acceptance Rate178of869submissions,20%
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