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研究生:羅英哲
研究生(外文):Ying-Zhe Luo
論文名稱:從光達點雲資料重建面特徵
論文名稱(外文):Reconstruction of Surface Features from LiDAR Data
指導教授:曾義星曾義星引用關係
指導教授(外文):Yi-Hsing Tesng
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:自然科學學門
學類:地球科學學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:87
中文關鍵詞:面擬合面重建區域成長法光達
外文關鍵詞:Surface featuressurface reconstructionLiDARsurface growing
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光達(又稱雷射掃瞄儀)具有快速獲取大量三維坐標點資訊的優點,可提供每秒數千點至數萬點的觀測數據,這些大量的點雲分佈幾何隱含著豐富的物面資訊,然而這些物面特徵資訊並非直接的幾何描述,必須轉換為數學函式或向量描述資料,才能成為可直接利用的顯性資訊。

本研究利用區域成長法的概念,搭配面擬合的計算,合併具有共面特性的點群,進而萃取出點雲中的面特徵。在區域成長的過程中,以鄰近擬合面的法向量夾角以及掃瞄點到擬合面的距離為合併的判斷依據,經由區域成長運算所集結的同類元素形成連結的區域,若每個元素視為一小擬合面,則連結的區域將可形成一個面特徵。本文中所發展的面重建方法可重建點雲中的平面、球面、圓柱面及多項式曲面等面特徵。

研究中針對數種地面光達點雲資料進行面重建實驗,得到相當良好的成果。所提的方法應用在空載光達點雲上,亦成功地運用於屋頂面萃取。本文之實驗亦針對面重建過程中所需要設定的預定參數,包括點雲的切割網格尺寸、角度門檻值、距離門檻值及種子的成長位置進行的探討,並以半自動化的方式由點雲資料來獲取預定參數設置的相關資訊,以提供使用者作為參考及設定依據。面重建後的成果,可提供具有相同面特性的點群及該面特徵的擬合參數,對於後續的點位量測或三維模型建置均有所助益。
Lidar (Laser Scanner) is capable of collecting a large number of 3D points, in which abundant surface features are implied in the distribution of point cloud data. However, these surface features should be extracted to from explicit information, i.e., it is necessary to transfer the point cloud data into mathematical expressions or vector data descriptions.

The proposed algorithm of surface reconstruction is based on the schemes of surface growing and surface feature fitting. It merges the co-plan points and extracts surface features from point cloud data. There are two factors to conduct the growing process: the angle between two normal vectors of adjacent patches and the distance of the point from the growing surface. Every merged cell is considered as a small patch, then the connect areas by region growing regarded as a surface feature. The reconstructive surface features in the proposed method includes planar features, spherical features, cylindrical features, and polynomial surface features.

The experimental data include ground-based Lidar and airborne Lidar. The overall results show the successful application examples of the proposed algorithm. In the experiment, the initial parameters such as grid sizes, threshold of angle, threshold of distance and the growing seed position are also discussed and extracted from point cloud data using a semi- automatic method. The results of reconstructive surface provide points cluster with the same surface characteristics and fitting parameter of the surface features. The extracted surface features will be useful for 3D modeling.
目錄
中文摘要…………………………………………………………………I
英文摘要 ………………………………………………………………II
目錄 ……………………………………………………………………IV
表目錄 …………………………………………………………………VI
圖目錄…………………………………………………………………VII

第一章 緒論…………………………………………………………1
§ 1-1 前言…………………………………………………………1
§ 1-2 研究動機與目的……………………………………………3
§ 1-3 研究方法與流程……………………………………………5

第二章 光達點雲的資料特性與處理………………………………7
§ 2-1 光達點雲的分佈情形………………………………………7
§ 2-1-1 掃瞄誤差與粗糙度 ………………………………10
§ 2-2 光達點雲特徵萃取的相關研究 …………………………16

第三章 面重建演算法 ……………………………………………19
§ 3-1 面重建演算法工作概念及流程 …………………………19
§ 3-2 三維規則網格分割 ………………………………………21
§ 3-3 散佈量和密度的估計 ……………………………………22
§ 3-3-1 散佈量的計算 ……………………………………23
§ 3-3-2 密度的計算 ………………………………………26
§ 3-4 特徵向量與角度門檻值的關係 …………………………29
§ 3-5 面擬合與距離門檻值的關係 ……………………………32
§ 3-5-1 擬合平面 …………………………………………34
§ 3-5-2 擬合圓柱面 ………………………………………35
§ 3-5-3 擬合球面 …………………………………………38
§ 3-5-4 擬合多項式曲面……………………………………39
§ 3-6 面特徵值與自動化種子搜尋機制………………………40

第四章 實驗成果與分析…………………………………………44
§ 4-1 實驗資料…………………………………………………44
§ 4-2 適當網格尺寸之決定……………………………………45
§ 4-2-1 測試牆面與考量因素……………………………45
§ 4-2-2 網格尺寸與密度的關係…………………………54
§ 4-2-3 網格尺寸與散佈量的關係………………………56
§ 4-3 地面光達資料面重建實驗………………………………60
§ 4-3-1 平面重建實驗……………………………………60
§ 4-3-2 球面重建實驗……………………………………65
§ 4-3-3 圓柱面重建實驗…………………………………66
§ 4-3-4 多項式曲面重建實驗……………………………68
§ 4-4 空載光達資料面重建實驗………………………………69

第五章 結論與建議…………………………………………………72

參考文獻………………………………………………………………74
附錄一…………………………………………………………………79
附錄二…………………………………………………………………81
湯凱佩,曾義星,『以八分樹三維網格結構組織光達點雲資料並進行平面特徵萃取』,第二十三屆測量學術及應用研討會論文集,pp. 143-150,2004

劉嘉銘,『光達點雲資料特徵萃取之研究』,國立成功大學測量工程研究所碩士論文,2005

賴志凱,『地面雷射掃瞄儀的精度分析與檢定』,國立成功大學測量及 空間資訊研究所碩士論文,2004

賴志恆,『雷射掃描點雲資料八分樹結構化之研究』,國立成功大學測量工程學系碩士論文,2003。

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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.,2006.
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