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Data-driven modeling for chinese ancient architectures
| Content Provider | ACM Digital Library |
|---|---|
| Author | Ren, Pu Huang, Youliang Shui, Wuyang Wu, Zhongke Zhou, Mingquan Zhang, Juan |
| Abstract | Chinese ancient architecture is well known for its unique shape styles and complex constructions, which results in a complicated 3D modeling process. In contrast to the existing procedural modeling method which generates architectures relying on fixed rules, our data-driven approach aggregate information from 3D model collections to realize analysis, inference and synthesis of components spontaneously. For proprietary properties of ancient building models, this paper describes the framework of the complete procedure from shape representation to component assembly. The plausible combinations for structural components are also learned from 3D model dataset by the Bayesian network. As a periodic research, some remaining works at each stage are proposed in this paper. We conclude these works with ideas that can inspire future research in the modeling issue for Chinese ancient architecture. |
| Starting Page | 59 |
| Ending Page | 62 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450346948 |
| DOI | 10.1145/3014027.3014029 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-12-03 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | 3d modeling Chinese ancient building Bayesian network Data-driven method |
| Content Type | Text |
| Resource Type | Article |
