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研究生:葉柏嘉
研究生(外文):Po-ChiaYeh
論文名稱:以線段偵測為基礎之半自動三維房屋模型重建方法
論文名稱(外文):A Semi-automatic Building Model Reconstruction Scheme based on Line Segmentation Detection
指導教授:饒見有饒見有引用關係
指導教授(外文):Jiann-Yeou Rau
學位類別:碩士
校院名稱:國立成功大學
系所名稱:測量及空間資訊學系碩博士班
學門:工程學門
學類:測量工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:78
中文關鍵詞:空載多相機攝影系統線段偵測器前方交會三維房屋模型
外文關鍵詞:Airborne Multiple Camera Imaging SystemLine Segment DetectorSpace Intersection3D Building Model
相關次數:
  • 被引用被引用:2
  • 點閱點閱:256
  • 評分評分:
  • 下載下載:19
  • 收藏至我的研究室書目清單書目收藏:0
在數碼城市和三維地理資訊系統的應用中,三維房屋模型扮演著非常重要的角色,相關應用包括都市發展與計劃、不動產管理、變遷分析等。因此如何有效且準確產生三維房屋模型,乃是相當重要的研究課題。本研究基於建物屋頂是由線段組合而成的假設,例如屋簷和屋脊,採用資料導向半自動化三維房屋模型重建的策略。資料來源為空載多相機攝影系統(AMCIS)包括五台高解析度DSLR數位相機,其中一台以垂直方式攝影,另外四台則傾斜約45度,經由相機率定和空三解算後得到內外方位參數。在重建房屋模型時,首先從所拍攝之數位影像中萃取線段,接著以人工匹配共軛線段,再以線-面交會為基礎的前方交會模式產生三維房屋結構線。最後再利用TMR(TIN-Merging and Reshaping)演算法重建三維房屋模型。研究中在偵測線型特徵時利用線段偵測器(Line Segment Detector, LSD)開放原始碼,其偵測精度可達次像元,且線段萃取成果可準確可靠的描述建物之邊界。而在線-面前方交會後所產生的物點三維坐標必須進一步擬合成三維直線,採用了奇異值分解法(Singular Value Decomposition, SVD)得到直線之方向向量,再決定線段之端點坐標,得到房屋三維結構線。本研究測試區位於台中市,測試的房屋屋頂型態包含平頂屋、山型屋、弧頂屋,實驗成果顯示本研究提出之方法除了圓弧邊界或屋頂之房屋外,可準確且成功的重建三維房屋模型。預期未來若將人工立體量測屋角點的程序改成屋簷線段的數化,或者延伸為全自動線段匹配,將可提升三維房屋模塑之效率。
Three-dimensional building model is one of the major components of a cyber-city and is vital for the realization of 3D GIS application such as urban development and planning, real estate management, change analysis, and so on. Therefore, how to improve the efficiency and accuracy of reconstructed building model is an important research issue. This paper presents a data-driven method for semi-automatic reconstruction of building models from 3D structural lines of a building, i.e. their eaves and ridges. The imagery were acquired by an airborne multiple cameras imaging system (AMCIS), which contains one vertical and four oblique DSLR cameras. The tilted cameras have an off-nadir viewing angles of about 45 degrees. The collected images were calibrated and triangulated to obtain accurate interior and exterior orientation parameters. During building model reconstruction, we detect line segment first and perform multiple lines matching manually. Then, a space intersection algorithm based on line-plane intersection is applied to obtain 3D roof structural lines. Finally, we utilize the TIN-Merging and Reshaping (TMR), which is a line-based roof model reconstruction algorithm, to achieve the goal of semi-automatic building modeling. In this study, during line segment detection, we utilize an open source called Line Segment Detector (LSD) that a sub-pixel accuracy could be obtained. The results can describe the outlines of roof boundary accurately and reliably. After manual multi-line matching the ground coordinates of a roof structural line was adjusted using a total least squares method which utilizes singular value decomposition (SVD) to avoid singularity issue. For performance evaluation, several case studies including different types of roofs, such as flat roofs, gable roofs, and cambered roofs, will be discussed. Experimental results indicate that except for circular or curved roofs or edges, the proposed method can successfully and accurately reconstruct 3D building models. It is expected that the proposed method can be used in stereo-plotting instead of conventional point-based approach. Meanwhile, for the purpose of increasing the efficiency of three dimensional building modeling the proposed method can be extended as a fully automatic multi-line matching procedure in the future.
摘要 I
Abstract II
致謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論 1
1-1 研究動機 1
1-2 研究目標、方法與流程 1
1-3 論文架構 2
第二章 文獻回顧 3
2-1 房屋模型 3
2-2 空載傾斜攝影 5
2-3 影像特徵萃取 6
2-3-1 點特徵 7
2-3-2 線特徵 8
2-3-3 面特徵 10
2-4 前方交會模式 11
2-4-1 點與點 11
2-4-2 面與面 12
2-4-3 線與面 13
第三章 研究資料與方法 14
3-1 使用資料 14
3-2 相機率定 20
3-3 空中三角測量 22
3-3-1 傳統空中三角測量 22
3-3-2 GPS輔助空中三角測量 23
3-4 線段偵測器 24
3-5 人工線段匹配 28
3-6 線-面前方交會 29
3-7 擬合直線 33
3-7-1 二維直線 33
3-7-2 三維直線 34
3-8 TMR三維房屋模塑 37
第四章 實驗成果與分析 38
4-1 空中三角測量 38
4-2 LSD 45
4-3 線-面前方交會夾角分析 49
4-4 房屋模塑精度分析 51
第五章 結論與未來建議 60
參考文獻 62
附錄 66
A-1 SIFT特徵匹配 66
A-2 SURF特徵匹配 69
A-3 TMR三維房屋模塑演算法 74
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