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| Content Provider | ACM Digital Library |
|---|---|
| Author | Cheng, Zhanglin Guo, Jianwei Xu, Shibiao Zhang, Xiaopeng |
| Abstract | Plants are ubiquitous in the nature, and realistic plant modeling plays an important role in a variety of applications. Over the last decades, an immense amount of efforts have been dedicated to plant modeling. These approaches can be classified into two major categories: procedural modeling [Palubicki et al. 2009; Stava et al. 2014] and data-driven reconstruction approaches (e.g., photographs [Li et al. 2011; Tan et al. 2007] or scanned points [Livny et al. 2010; Xu et al. 2007]). Each approach has its own pros and cons. For example, procedural modeling approaches work well for synthesizing local branch structure details to produce botanically correct trees, but they lack the ability to control the growth of trees under certain shape constraints. While the data-driven approaches might precisely reconstruct skeletal structures, the botanical fidelity of trees are difficult to maintain. |
| Starting Page | 1 |
| Ending Page | 2 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781450350150 |
| DOI | 10.1145/3102163.3102193 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-07-30 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Point cloud Rule-based modeling Procedural plant generation |
| Content Type | Text |
| Resource Type | Article |
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