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系統識別號 U0026-1103201820334400
論文名稱(中文) 分析基於三維空間點雲的曲面重建方法:過濾泊松與B樣條
論文名稱(英文) Analysis of 3D Point Cloud-Based Surface Reconstruction Methods: Screened Poisson Vs. B-Spline
校院名稱 成功大學
系所名稱(中) 資訊工程學系
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 106
學期 1
出版年 106
研究生(中文) 李旻
研究生(英文) Min Li
學號 P76041093
學位類別 碩士
語文別 英文
論文頁數 83頁
口試委員 指導教授-郭淑美
共同指導教授-連震杰
口試委員-謝孫源
口試委員-蘇銓清
口試委員-蔡玉娟
中文關鍵字 點雲  B樣條  多階層B樣條逼近  泊松方程  過濾泊松方程  逆向工程 
英文關鍵字 Point cloud  B-spline  Multilevel B-spline Approximation  Poisson  Screened Poisson Equation  Reverse Engineering 
學科別分類
中文摘要 曲面重建,是一個利用掃描資料組建的物體表面形狀的過程。藉由各種不同的掃描方法,我們能以離散的方式,獲得有興趣的物體表面的形狀資訊,而後通過這些離散的點資訊再重新構築為更密集的點甚至是連續的表面。近年來3D列印的技術較為成熟,價格也有所降低,使得相關設備的使用日漸眾多。本實驗室提出一個架構,採用非接觸式的3D掃描設備獲取物體資訊,並以3D列印設備收尾,建立了一個完整的三維逆向工程系統。而本論文著眼於分析和比較曲面重建方法中,針對輸入點雲的可靠性較高的案件的二種演算法,並且結合二種演算法,提出適用於我們的實際案件的架構。在物體的掃描結果本身較完整保留幾何和拓樸資訊的情況下,重建出三維逆向工程中所需的連續曲面並交予3D列印設備後續重建出物體的模型。
英文摘要 Surface reconstruction is a process that uses scanned point cloud to construct the original surface of an object. By using some different scanning methods, we can obtain the information of the surface of the object that we interested in, and then reconstruct these information into much more intensive point clouds or even continuous surface. In recent years, due to the maturity of 3D printing technology, the price of 3D printing tools have decreased. The laboratory proposed a framework that acquires information of objects using non-contact 3D scanning device and gets reconstructed models using 3D printing tools to make the whole system fully operational.
This research is focus on analyzing and comparing the two algorithms which face to the cases having high reliability of point clouds, and further proposed the framework combing to methods to deal with the object that we interested in. Which means that we can reconstruct the surface of objects by using point clouds which have geometry and topology information kept in intact and then get the model using 3D printer.
論文目次 摘要 IV
Abstract V
誌謝 VI
Table of Contents VIII
List of Figures X
List of Tables XIV
Chapter 1 1
1.1 Motivation 1
1.2 Relative Work 6
1.3 Contribution 13
Chapter 2 15
2.1 B-spline Mathematical Definition 15
2.2 Framework of Multilevel B-spline Approximation 27
2.3 Implementation detail of MBA Algorithm 30
2.4 Optimization of MBA algorithm 38
Chapter 3 41
3.1 Framework of Screened Poisson Reconstruction 42
3.2 Definition of Indicator Function 43
3.3 Implementation detail of Screened Poisson Reconstruction 44
Chapter 4 57
4.1 Framework of Proposed Method 57
4.2 Normal Estimation using SVD with KD Tree 60
4.3 Analyze of Proposed Method 61
Chapter 5 62
5.1 Data Collection 62
5.2 Reconstruction results 68
Chapter 6 79
Reference 82

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[3] Les Piegl and Wayne Tiller, “The NURBS Book,” 2nd Edition 1997.
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[9] TAGLIASACCHI, A., OLSON, M., ZHANG, H., HAMARNEH, G.,AND COHEN-OR, D. 2011. Vase: Volume-aware surface evolution for surface reconstruction from incomplete point clouds.Computer Graphics Forum (Proc. Eurographics Symp. on Geometry Processing) 30, 5, 1563–1571.
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[12] YANG, H. P., WANG, W., AND SUN, J. G. 2004. Control point adjustment for b-spline curve approximation. Comput.-aided Design 36, 639–652.
[13] YIN, K., HUANG, H., ZHANG, H., GONG, M., COHEN-OR, D., AND CHEN, B. 2014. Morfit: Interactive surface reconstruction from incomplete point clouds with curve-driven topology and geometry control. ACM Trans. on Graphics (Proc. of SIGGRAPH Asia) 33, 6, 41:1–41:12
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