臺灣博碩士論文加值系統

地面光達系統可以快速獲取大量且高精度之點雲資料，這些點雲資料不但記錄了被掃描物體之三維資訊，還包含其色彩訊息。但因光達點雲資料量過於龐大，若要直接於電腦上展示其三維模型，必須配合有效的資料處理技術，才能迅速且即時地將資料顯示於螢幕上。

我們針對地面光達系統獲取之建物點雲，提出一套處理方法，期盼透過少數關鍵點雲，就足以表示整個建物的模型。研究流程主要分為三階段，首先採用三維網格資料結構，從地面光達系統獲取之建物點雲中，萃取出關鍵點雲，並利用三維不規則三角網建模方式，進行模型建構工作，產生建物大略模型。其次再逐點判斷是否將剩餘之點加入此模型中，持續更新模型細微之部分。最後將點雲中的色彩資訊轉成影像，敷貼在模型表面上，讓整個模型更為逼真。

我們以政大綜合大樓進行實驗，成功地減少大量冗餘的點雲資料，只需要約原始點雲的1％，就足以將綜合大樓模型建構完成。為了達到可以從不同視角即時瀏覽建物模型，我們採用虛擬實境語言(VRML)來描述處理後的三維模型，遠端使用者只需透過一般網頁瀏覽器，即可即時顯示處理過的三維建物模型。

Ground-based LIDAR system can be used to detect the surface of the buildings on the earth. In general, it produces large amount of high-precision point cloud data. These data include not only the three-dimensional space information, but also the color information. However, the number of point cloud data is huge and is difficult to be displayed efficiently. It’s necessary to use efficient data processing techniques in order to display these point cloud data in real-time.

In this research, we construct the three-dimensional building model using the key points selected from a given set of point cloud data. The major works of our scheme consists of three parts. In the first part, we extract the key points from the given point cloud data through the help of a three-dimensional grid. These key points are used to construct a primitive model of the building. Then, we checked all the remaining points and decided whether these points are essential to the final building model. Finally, we transformed the color information into images and then used the transformed images to represent generic surface material of the three-dimensional model of the building. The goal of the final step is to make the model more realistic.

In the experiments, we used the twin-tower of our university as our target. We successfully reduced the required data in displaying the building model and only about one percent of the original point cloud data are used in the final model. Hence, one can see the twin-tower from various view points in real-time. In addition, we use VRML to describe our model and the users can browse the results in real-time on internet.

第一章 緒論 1
1.1研究動機與目的 1
1.2問題描述 2
1.3系統架構與流程說明 3
1.3.1地面光達點雲重建三維模型 4
1.3.2處理點雲色彩資訊進行影像敷貼 5
1.4本論文的貢獻 6
1.5論文章節架構 7
第二章 相關研究 8
2.1簡介地面光達系統 9
2.1.1地面光達系統 9
2.1.2地面光達系統掃描原理 10
2.2資料整合重建三維模型 11
2.3影像敷貼 12
第三章 利用地面光達點雲資料重建三維模型 13
3.1三維網格資料結構 14
3.2適應性網格模型 15
3.3建構不規則三角網 17
3.4建構細部三角網 19
第四章 自動化影像敷貼 21
4.1儀器觀測站坐標偵測 22
4.1.1去除雜訊 24
4.1.2邊緣偵測 29
4.1.3霍夫轉換 31
4.1.4儀器觀測站坐標估算 35
4.2影像取樣 36
4.3影像敷貼 38
第五章 實驗結果 40
5.1適應性網格模型 42
5.2建構不規則三角網 44
5.3建構細部三角網 45
5.4儀器觀測站坐標偵測 46
5.4.1去除雜訊結果 47
5.4.2邊緣偵測結果 50
5.4.3儀器觀測站坐標估算 51
5.5影像取樣結果 54
5.6影像敷貼結果 57
第六章 結論 59
6.1結論 59
6.2未來發展 60
參考文獻 62

[1] 余徐維、方偉凱、詹進發，”利用地面LIDAR資料建立三維建物模型”，第二十四屆測量學術及應用研討會論文集，pp. 483-490，2005。
[2] 陳良健、郭志奕、饒見有，”整合點雲與輪廓線模塑建物模型之研究”，第二十四屆測量學術及應用研討會論文集，pp. 293-300，2005。
[3] 曾義星、賴志凱，”地面光達掃描定位原理與誤差分析”，測量工程，第四十六卷，第四期，pp. 3-22，2004。
[4] 曾義星、史天元，”三維雷射掃描技術及其在工程測量上之應用”，中國土木水利工程學刊，2004。
[5] 曾義星、史天元，"三維雷射掃描儀─新一代測量利器"，科學發展月刊，365期，pp.16-21，2003。
[6] 劉燈烈，”地面光達點雲資料的平差結合與影像敷貼”，國立成功大學測量及空間資訊學系碩士論文，2004。
[7] Azernikov, S. and A. Fischer, “Anisotropic Meshing of Implicit Surfaces”, IEEE International Conference on Shape Modeling and Applications, June 13 - June 17, MIT, Boston, USA (slides) , 2005.
[8] Castro-Díaz, M. J., F. Hecht, and B. Mohammadi, “New Progress in Anisotropic Grid Adaptation for Inviscid and Viscous Flows Simulations”, Proceedings of the 4th International Meshing Roundtable, pp. 73-85, 1995.
[9] De Berg, M., M. van Kreveld, M. Overmars, and O. Schwarzkopf, “Computational Geometry: Algorithms and Applications”, Second Edition, Springer, 2000.
[10] Dey, T. K., J. Giesen, and J. Hudson, “Delaunay Based Shape Reconstruction from Large Data”, IEEE Symposium on Parallel and Large Data Visualization, pp. 19-27, 2001.
[11] Fang, T. P. and L. A. Piegl, “Delaunay Triangulation in Three Dimensions”, IEEE Computer Graphics and Applications, volume 15, No. 5, pp. 62-69, 1995.
[12] Gonzalez, R. C. and R. E. Woods, "Digital Image Processing", Second Edition, Prentice Hall, 2002.
[13] Heckbert, Paul, "Survey of Texture Mapping", IEEE Computer Graphics and Applications, volume 6, pp. 56–67, Nov., 1986.
[14] Leica Geosystems, HDS3000 3D Laser Scanner Specifications, 2004: http://www.leica-geosystems.com/hds/en/lgs_6506.htm
[15] Lorensen, W. E. and H. E. Cline, “Marching cubes: A high resolution 3D surface construction algorithm”, ACM Computer Graphics (SIGGRAPH ’87 Proceedings), volume 21, pp. 163–170, 1987.
[16] Wolf, P. R. and B. A. Dewitt, “Elements of photogrammetry with applications in GIS”, McGraw-Hill, pp.303-305, 2000.