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Synthesizing trees by plantons

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Abstract

In this paper, we present a two-level statistical model for characterizing the stochastic and specific nature of trees. At the low level, we define plantons, which are a group of similar organs, to depict tree organ details statistically. At the high level, a set of transitions between plantons is provided to describe the stochastic distribution of organs.

Based on such a tree model, we propose a novel tree modeling approach, synthesizing trees by plantons, which are extracted from tree samples. All tree samples are captured from the real world. We have designed a maximum likelihood estimation algorithm to acquire the two-level statistical tree model from single samples or multi- samples. Experimental results show that our new model is capable of synthesizing new trees with similar, yet visually different shapes.

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Authors and Affiliations

  1. State Key Lab of CAD&CG, Zhejiang University, Zhejiang, P.R. China

    Rui Wang, Wei Hua, Zilong Dong, Qunsheng Peng & Hujun Bao

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  1. Rui Wang
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  2. Wei Hua
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  3. Zilong Dong
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  4. Qunsheng Peng
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  5. Hujun Bao
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Correspondence to Wei Hua.

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Wang, R., Hua, W., Dong, Z. et al. Synthesizing trees by plantons. Visual Comput 22, 238–248 (2006). https://doi.org/10.1007/s00371-006-0002-x

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