LOD generation for 3D polyhedral building model

Jiann-Yeou Rau, Liang Chien Chen, Fuan Tsai, Kuo Hsin Hsiao, Wei Chen Hsu

研究成果: Conference contribution

10 引文 (Scopus)

摘要

This paper proposes an algorithm for the automatic generation of Levels-of-Detail (LODs) for 3D polyhedral building models. In this study a group of connected polyhedrons is considered as "one building", after which the generalization is applied to each building consecutively. The most detailed building models used is the polyhedral building model which allows for an elaborate roof structure, vertical walls and a polygonal ground plan. In the work the term "Pseudo-Continuous LODs" is described. The maximum distinguishable "feature resolution" can be estimated from the viewer distance to a building and is used to simplify the building structure by the polyhedron merging and wall collapsing with regularization processes. Experimental results demonstrate that the number of triangles can be reduced as a function of the feature resolution logarithm. Some case studies will be presented to illustrate the capability and feasibility of the proposed method including both regular and irregular shape of buildings.

原文English
主出版物標題Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings
頁面44-53
頁數10
DOIs
出版狀態Published - 2006 十二月 1
事件1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006 - Hsinchu, Taiwan
持續時間: 2006 十二月 102006 十二月 13

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4319 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Other

Other1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006
國家Taiwan
城市Hsinchu
期間06-12-1006-12-13

指紋

Polyhedron
Collapsing
Merging
Logarithm
Roofs
Irregular
Triangle
Regularization
Simplify
Vertical
Experimental Results
Term
Demonstrate
Buildings
Generalization

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

引用此文

Rau, J-Y., Chen, L. C., Tsai, F., Hsiao, K. H., & Hsu, W. C. (2006). LOD generation for 3D polyhedral building model. 於 Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings (頁 44-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 4319 LNCS). https://doi.org/10.1007/11949534-5
Rau, Jiann-Yeou ; Chen, Liang Chien ; Tsai, Fuan ; Hsiao, Kuo Hsin ; Hsu, Wei Chen. / LOD generation for 3D polyhedral building model. Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. 2006. 頁 44-53 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Rau, J-Y, Chen, LC, Tsai, F, Hsiao, KH & Hsu, WC 2006, LOD generation for 3D polyhedral building model. 於 Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 4319 LNCS, 頁 44-53, 1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006, Hsinchu, Taiwan, 06-12-10. https://doi.org/10.1007/11949534-5

LOD generation for 3D polyhedral building model. / Rau, Jiann-Yeou; Chen, Liang Chien; Tsai, Fuan; Hsiao, Kuo Hsin; Hsu, Wei Chen.

Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. 2006. p. 44-53 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 4319 LNCS).

研究成果: Conference contribution

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Rau J-Y, Chen LC, Tsai F, Hsiao KH, Hsu WC. LOD generation for 3D polyhedral building model. 於 Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. 2006. p. 44-53. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11949534-5