以地面及空載光達點雲重建複雜物三維模型

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姓名

洪祥恩(Hsiang-en Hung) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

以地面及空載光達點雲重建複雜物三維模型
(Reconstruction of 3D Models for Complex Buildings from Ground-based and Airborne LIDAR Point Cloud Data)

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摘要(中)

光達是近年來一個受重視的新光學遙感探測技術。對於三維模型重建而言，雷射掃描點雲資料具相當價值，能細緻地重建建物表面，如牆面、屋頂面、柱子、窗戶等細部的物件特徵。由於點雲資料為一群離散的三維座標點群，難以直接利用原始資料中所隱含的三維資訊，因此在產生三維建物模型前，必須先經過前處理，例如：組織不規則三角網、點雲資料區塊化、結構特徵辨識、結構特徵萃取等等。
以光達點雲重建三維房屋模型可達高細緻度層級，但由於獲取資料形式之限制，欲得到精細準確的三維模型，重建過程繁複。本研究以空載及地面光達點雲為資料來源，重建符合 OGC CityGML LOD3 層級規範的三維房屋模型。過程主要分為三個部分：光達點雲資料套合、點雲群組化及三維表面重建。首先對目標測區獲取空載及地面光達點雲資料後，以七參數轉換方式對空載及地面點雲進行套合。接著根據點雲之幾何條件如共面條件等，將點雲群組化，使同群點雲具相同幾何條件。接著，以不同策略針對平面點群及曲面點群重建三維表面，最後整合重建結果產生完整三維模型，並敷貼高解析紋理影像於模型表面。重建之模型並以地面實測方式驗證模型精度。

摘要(英)

LIDAR, Light Detection And Ranging, is an emerging technique for optical remote sensing recently. Laser scanned point cloud is a valuable data source for building reconstruction because it can recover detailed building façade structures like wall, roof, pillar and window etc. Since the point cloud data are discrete, it is difficult to acquire useful 3D information directly. Therefore, before the generation of building models, necessary pre-processing, such as triangulated irregular network (TIN) organization, segmentation, or feature extraction etc., must be carried out.
Modeling from point cloud data can achieve high level of detail. However, due to the limitation of data, there will be complex procedures to reconstruct a highly accurate model. This research aims to reconstruct building models conforming to OGC CityGML LOD3 standard from LIDAR point clouds. The proposed method is divided into three main parts: data registration, points partitioning and surface reconstruction. First, after acquiring point cloud data from airborne and ground-based LIDAR, they are merged to a single dataset using 7-parameter transformation. The merged point cloud data are then partitioned into several groups according to different conditions such as coplanarity etc. For each point group, a three-dimensional surface is constructed based on Least Squares Method. Finally all surfaces are merged to reconstruct 3D models, and high resolution images are used as façade texture. The accuracy of reconstructed models are evaluated with ground measurement of check points.

關鍵字(中)

★ 光達
★ 點雲資料
★ 模型重建
★ 最小二乘法
★ 細緻度層級
★ 群組化

關鍵字(英)

★ LIDAR
★ Point Cloud
★ Model Reconstruction
★ Partition
★ Least Squares Method (LSM)
★ Level of Detail (LOD)

論文目次

摘要 I
ABSTRACT II
致謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章序論 1
1.1 研究背景 1
1-2 細緻化層級 (Level of Detail, LOD) 3
1-3 光達及光達點雲資料 4
1-4 研究動機與目的 6
1-5 論文架構 10
第二章文獻回顧 12
2-1 以航照資料重建三維模型 12
2-2 光達點雲資料重建三維模型 13
2-3 融合資料重建三維模型 15
2-4 點雲群組化方法回顧 16
第三章研究方法與流程 19
3-1 研究方法綜述 19
3-2 資料前處理 (Point data pre-processing) 22
3-3 點雲資料套合 (registration) 27
3-4 點雲群組化 (partitioning) 31
3-5 模型三維表面重建 (surface reconstruction) 36
3-5-1 平面點雲表面重建 (Plane points reconstruction) 40
3-5-2 曲面點群表面重建 (Curve points reconstruction) 42
第四章實驗成果與分析 48
4-1 儀器簡介 48
4-2 控制點取得與驗證指標 52
4-2-1 自由測站法 52
4-2-2 驗證指標 55
4-3 實驗案例一 56
4-4 實驗案例二 72
第五章結論及未來展望 89
參考文獻 92

參考文獻

王冠華，2003，多重疊航照立體對半自動房屋模型重建，碩士論文，國立中央大學土木工程學系。
李啟泓，2005，穩健線性預估法應用於空載光達點雲過濾之研究，碩士論文，國立成功大學測量及空間資訊學系。
周富晨、曾義星，2005，適應性點雲過濾演算法於空載光達資料產生數值高程模型之研究，航測及遙測學刊，第十卷，第一期，第71-88頁。
陳良健、李唐宇，2008，結合多元資料重建三維模型，航測及遙測學刊，第十三卷，第三期，第159-168 頁。
陳正穎、陳良健，2000，多重疊航測影像中人工建築物三維模型之重建，航測及遙測學刊，第五卷，第三期，第1-13頁。
陳衍豪，2001，立體航測影像直線與圓弧輪廓建物，碩士論文，國立中央大學土木工程學系。
張智安、陳良健，2009，整合空載光達點雲與地形圖模塑房屋之分治策略，航測及遙測學刊，第十四卷，第二期，第83-94頁。
賴泓瑞，2009，以模型樣板為基礎之建物三維點雲建模演算法，碩士論文，國立成功大學測量及空間資訊學系。
閻平，2005，LIDAR數據中多層次、多直角房屋的三維重建，碩士論文，武漢大學。
Baillard, C. and Zisserman, A., 2000. A plane sweep strategy for the 3D reconstruction of buildings from multiple images, International Archives of Photogrammetry and Remote Sensing, Vol. 33, Part B2, Amsterdam, Netherlands, pp. 56-62.
Chen, L. -C., Kuo, C.-Y. and Rau, J.-Y., 2004. Fusion of LIDAR Data and Large-scale Vector Maps for Building Reconstruction, Proc. 2004 Asian Conference on Remote Sensing, Thailand , No. B-2.6.
Filin, S., 2002. Surface clustering from airborne laser scanning data, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXIV, part 3A/B, Graz, Austria, pp. 119-124.
Grote, B.G.H., 2002. Segmentation of tin-structured surface models, Joint Conference on Geo-spatial theory, Processing and Applications, Ottawa, Canada, 8-12 July 2002.
Gröger, G., Kolbe , T. H., Czerwinski, A. and Nagel, C., 2008. OpenGIS® City Geography Markup Language (CityGML) Encoding Standard, OpenGIS® Encoding Standard, Version 1.0.0, OGC 08-007r1, 2008-08-20.
Jaw, J.J. and Chuang, T.Y., 2010. LIDAR Point Clouds Registration Based on Multiple Features, Workshop on Unconventional Photogrammetry, Tainan, Taiwan, April 1-2, pp.190-200.
Lee, D.S., Shan, J. and Bethel, J.S., 2003. Class-guided building extraction from IKONOS imagery, Photogrammetric Engineering and Remote Sensing, Vol. 69, No. 2, pp. 143-150.
Pu, S. and Vosselman, G., 2006, Automatic Extraction of Building Features from Terrestrial Laser Scanning, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 36, part 5, Dresden, Germany, September 25-27, 5 p. (on CD-ROM).
Pu, S., 2007, Automatic building modelling from terrestrial laser scanning, Advanced in 3D Geoinformation Systems, Springer, December 12-14, pp. 147-16
Pu, S., 2008, Generating Building Outlines From Terrestrial Laser Scanning, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B5, Beijing 2008.
Rabbani, T., van den Heuvel, F.A. and Vosselman, M.G., 2006. Segmentation of point cloud using smoothness constraints, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVI, part 5, Dreden Germany, pp. 248-253.
Suveg, I. and Vosselman, G., 2004. Reconstruction of 3D building models from aerial images and maps, ISPRS Journal of Photogrammetry and Remote Sensing Volume 58, Issues 3-4, January 2004, Pages 202-224.
Tarsha-Kurdi, F., Landes, T. and Grussenmeyer, P., 2007. Hough-Transform and Extended RANSAC Algorithms for Automatic Detection of 3D Building Roof Planes from Lidar Data, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVI, part 3/W52, Espo, Finland, pp. 407-412.
Tseng, Y.H. and Wang, S. 2003. Semi-Automated Building Extraction based on CSG Model-Image Fitting, Photogrammetric Engineering & Remote Sensing, Vol. 69, No. 2, pp. 171-180.
Vosselman, G., Gorte, B.G.H., Sithole, G. and Rabbani, T., 2004. Recognising Structure in Laser Scanner Point Clouds, International Archives of Photogrammetry, Remote Sensing and Spatia Information Sciences, vol. 46, part 8/W2, Freiburg, Germany, October 4-6, pp. 33-38.
Wang, Z. and Schenk, T., 2000. Building Extraction and Reconstruction from LIDAR Data. International Archives of Photogrammetry and Remote Sensing, CD-ROM.
Wehr, A. and Lohr, U., 1999. Airborne Laser Scanning – An Introduction and Overview, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 54, pp. 68-82.
Wolf, P. R. and Dewitt, B. A., 2000. Element of Photogrammrtry with Application in GIS, McGraw Hill press, 3rd edition.
Zhao, F., Huang, Q. and Gao, W., 2006. Image Matching by Normalized Cross-Correlation, In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP2006. May 2006, Volume 2, pp. IIII, 14-19.

指導教授

蔡富安(Fuan Tsai)

審核日期

2011-8-18

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