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A hybrid modeling method of Chinese ancient architecture

Published: 08 December 2008 Publication History

Abstract

In this paper, we present a hybrid of graph-based and neural network modeling system of Chinese Ancient Pagoda (CAP). To implement the pagoda modeling system, we have built a basic element model library of pagoda by L system and a corresponding feature library. Feature points have been detected by our feature points extraction algorithm. After the Feature Segment Graph (FSG) is transformed into representation vectors, and these vectors are presented to the neural network which classifies them into feature classes. Once the feature information is detected, a virtual assembly process ensures the coherent architecture styles of CAP. The most important characteristic of this method is realistic modeling and rapid generating, so it can be applied to promising applications in entertainment industry.

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cover image ACM Conferences
VRCAI '08: Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
December 2008
223 pages
ISBN:9781605583358
DOI:10.1145/1477862
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 December 2008

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Author Tags

  1. L system
  2. Pagoda
  3. architecture
  4. feature points
  5. modeling
  6. neural network

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