結合光達資料與大比例尺向量圖重建三維建物模型

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姓名

郭志奕(Chih-Yi ,KUO) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

結合光達資料與大比例尺向量圖重建三維建物模型
(Fusion of LIDAR Data and Large-Scale Vector Map for Building Reconstruction)

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摘要(中)

數碼城市日益重要。而在數碼城市中，建物為其必要單元。光達資料(LIDAR data)的引進，為自動化建物重建之研究方向帶來可能性。
大比例尺向量圖具有精確之二維屋緣線，而光達資料具有豐富之屋頂面資訊。故本研究欲結合以上兩種資料之優勢，進行三維建物重建。本研究工作流程主要分為三部分：(1)資料整合、(2)建物頂共面分析、及(3)建物模塑。在資料整合部分，內容為兩資料之前處理，光達資料需去除地表起伏，而向量圖需建構封閉多邊型。在建物頂共面分析部分，以區塊成長法進行牆面和屋頂面之偵測。最後在建物模塑部分，內容為求取建物三維結構線段，並以整體平差進行建物幾何約制調整。
本研究並以台中大坑進行測試。光達資料點密度約 1.71(點/平方公尺)，向量圖比例尺為1:1000，重建完全正確率約90%，模塑誤差為0.17m。

摘要(英)

Cyber city is getting important due to the developments of computer technology and the demands from city management. Building models, among others, could be the most important elements in a cyber city. Due to its maturity, LIDAR data has demonstrated profound potentials in fully automatic building reconstruction.
LIDAR data contains plenty of height information, while vector maps preserve accurate building boundaries. From the viewpoint of data fusion, we try to integrate LIDAR data and large-scale vector maps to perform building modeling. The proposed scheme comprises three major steps: (1) preprocessing of LIDAR data and vector maps, (2) segmentation and detection of wall faces and roof faces, and (3) building modeling. In the preprocessing of LIDAR data, the height variation of the above-ground objects is determined by subtracting the surface elevation from the terrain. The closed polygons for buildings are also obtained. In next stage, segmentation and detection of wall faces and roof faces is implemented by region growing. In the step of the building modeling, the construct edges of a building can be obtained. We also implement the geometric constraints by least squares adjustment.
The test data covers Tai-Chung city in the middle of Taiwan. The average density of LIDAR data is about 1.71 points per square meter. The vector maps are with a scale of 1:1,000. About 90% buildings are correctly reconstructed by the proposed method. The shaping error is about 0.17m.

關鍵字(中)

★ 迪式三角網
★ 三維建物重建
★ 向量圖
★ 光達資料

關鍵字(英)

★ Triangulated Irregular Network
★ Vector Maps
★ Building Reconstruction
★ LIDAR

論文目次

目錄
摘要 I
ABSTRACT II
致謝 III
目錄 IV
圖目錄 VI
表目錄 IX
第一章前言 1
1.1研究動機與目的 1
1.2文獻回顧 3
1.3研究構想與流程 7
1.3.1資料整合 7
1.3.2建物頂共面分析 8
1.3.3建物模塑 9
第二章資料整合與建物頂共面分析 11
2.1資料前處理 12
2.2萃取建物點雲 14
2.2.1判斷點於多邊型內 14
2.2.2以群聚法萃取建物點雲 15
2.3建構迪氏三角網 17
2.4建物頂共面分析 19
2.4.1以區塊成長法進行牆面偵測 20
2.4.2以區塊成長法進行屋頂面偵測 21
2.5迴歸屋頂面方程式 23
第三章建物模塑 24
3.1求取屋脊三維線段 25
3.2修正屋脊三維線段 27
3.3求取階梯線三維線段 30
3.4修正階梯三維線段 33
3.5求取外部結構三維線段 35
3.6建物幾何約制調整 39
3.6.1局部幾何約制調整 39
3.6.2整體幾何約制調整概念 40
3.7幾何約制整體平差 40
3.7.1設定幾何約制條件 40
3.7.2建構條件方程式 41
3.7.3整體平差至最或然解 46
第四章測試成果與討論 47
4.1研究資料簡介 47
4.2研究流程中各門檻值之討論 50
4.3資料整合之成果與討論 53
4.3.1去除地表起伏之成果 53
4.3.2資料套合之成果 55
4.4建物模型模塑之成果與討論 56
4.4.1測區重建成果 58
4.4.2平頂屋和簡易山型屋測試 59
4.4.3複雜山型屋測試(1) 60
4.4.4複雜山型屋測試(2) 62
4.4.5複雜山型屋測試(3) 64
4.4.6複雜山型屋測試(4) 66
4.4.7複雜山型屋測試(5) 68
4.4.8非平面屋頂建物 71
4.4.9其他建物測試 72
4.4.10測試錯誤例(1) 74
4.4.11測試錯誤例(2) 75
第五章結論與建議 79
參考文獻 82

參考文獻

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指導教授

陳良健(Liang-Chien Chen)

審核日期

2005-7-17

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