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Data-driven modeling and animation of outdoor trees through interactive approach

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Abstract

Computer animation of trees has widespread applications in the fields of film production, video games and virtual reality. Physics-based methods are feasible solutions to achieve good approximations of tree movements. However, realistically animating a specific tree in the real world remains a challenge since physics-based methods rely on dynamic properties that are difficult to measure. In this paper, we present a low-cost interactive approach to model and animate outdoor trees from photographs and videos, which can be captured using a smartphone or handheld camera. An interactive editing approach is proposed to reconstruct detailed branches from photographs by considering an epipolar constraint. To track the motions of branches and leaves, a semi-automatic tracking method is presented to allow the user to interactively correct mis-tracked features. Then, the physical parameters of branches and leaves are estimated using a fast Fourier transform, and these properties are applied to a simplified physics-based model to generate animations of trees with various external forces. We compare the animation results with reference videos on several examples and demonstrate that our approach can achieve realistic tree animation.

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Acknowledgements

We thank Hironori Yoshida, Seung-tak Noh and the anonymous reviewers. This work was supported by NSFC [61303124], National 863 Plan [2013AA102304 02] and NSBR Plan of Shaanxi [2015JQ6250].

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Authors and Affiliations

  1. College of Information Engineering, Northwest A&F University, Xianyang, China

    Shaojun Hu & Zhiyi Zhang

  2. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

    Haoran Xie & Takeo Igarashi

Authors
  1. Shaojun Hu
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  2. Zhiyi Zhang
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  3. Haoran Xie
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  4. Takeo Igarashi
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Corresponding author

Correspondence to Shaojun Hu.

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Hu, S., Zhang, Z., Xie, H. et al. Data-driven modeling and animation of outdoor trees through interactive approach. Vis Comput 33, 1017–1027 (2017). https://doi.org/10.1007/s00371-017-1377-6

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  • DOI: https://doi.org/10.1007/s00371-017-1377-6

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