| 研究生: |
王聖鐸 Wang, Sendo |
|---|---|
| 論文名稱: |
以浮測模型理論萃取三維空間資訊-以建物重建為例 Theory of Floating Model in 3D Spatial Information Extraction – A Case Study on Building Reconstruction |
| 指導教授: |
曾義星
Tseng, Yi-Hsing |
| 學位類別: |
博士 Doctor |
| 系所名稱: |
工學院 - 測量及空間資訊學系 Department of Geomatics |
| 論文出版年: | 2005 |
| 畢業學年度: | 93 |
| 語文別: | 中文 |
| 論文頁數: | 169 |
| 中文關鍵詞: | 浮測模型 、建物重建 、數值攝影測量 、三維空間資訊 |
| 外文關鍵詞: | Floating Model, Digital Photogrammetry, Building Reconstruction, 3D Spatial Information |
| 相關次數: | 點閱:110 下載:4 |
| 分享至: |
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三維城市模型(3D City Model)或三維空間資訊系統(3D Spatial Information System)整合並提供各方面所需的三維空間資訊,可以廣泛應用在都市計畫、市政管理、不動產管理、交通規劃、機場航道規劃、無線基地台規劃、觀光導覽、國安維護等民生及專業用途。數十年來攝影測量一直被認為是最有效且精確的測繪技術,然而傳統以浮測標(Floating Mark)逐點量測的方式建置三維城市模型時,操作員需要專注於屋角點的量測及點位之連結,是三維空間資訊萃取的瓶頸。本研究採用模型式建物萃取法(Model-based Building Extraction),將傳統的浮測標擴充為浮測模型(Floating Model),使量測的單元不再是抽象的一個點位,而是許多種可伸縮、旋轉、移動的三維模型,期能以逐物件萃取的方式提升三維空間資訊之萃取效率。延伸浮測標量度的概念為浮測模型,即是將零維的浮測標拓展到三維實體,除了如同浮測標具備可調整的三維位置參數外,還依模型種類增加了各方向的伸縮尺度、空間旋轉等參數,可想像成一個漂浮在空間中,可移動、旋轉、縮放大小以量測地物的模型。將浮測模型投影至所有影像,並套合至影像上的目標地物,便有如回復攝影瞬間之幾何空間條件,此時之模型參數與影像外方位元素即為最佳解,此即以浮測模型萃取三維空間資訊之基本理論。本研究建置了點、線、面、立體四大類基本元件模型庫,量測員可以依需要選擇適當元件模型,在多張重疊像片上進行模型式的量度。並可依模型精細程度需求,以數個基本元件模型分部萃取,再透過布林運算規則組合為複合模型,因此能適用於萃取大多數的三維建物。以浮測模型為基礎,本研究提出一套半自動化萃取策略,操作員透過人機互動介面將模型一次套合至所有影像,再透過最小二乘模型-影像套合演算法自動計算最佳套合,以便在已知相片方位的條件下,利用浮測模型萃取地物的三維空間資訊,或在已知地物模型資訊的條件下利用模型求解相片的外方位元素。透過實驗案例證明,所提的浮測模型理論確可有效地應用於建物三維空間資訊之萃取,提高三維塑模之效率,並能達到傳統攝影測量之精度要求。
3D city model or 3D spatial information system integrates 3D spatial information and thus can be applied to versatile applications such as urban planning, real estate managing, traffic evaluating, radio station locating, tourist guiding etc. Photogrammetry has been considered as the most efficient technique for extracting 3D spatial information in the last few decades. However, the operator has to measure the 3D coordinates of all points and connect the adjacent points in sequence. This point-by-point measurement of using floating mark has become the bottleneck while reconstructing the 3D city model. In this paper, we expanded the floating mark to the floating model based on the concept of model-based building extraction. The measuring tool is no longer only an abstract point but also many kinds of 3D model, which can be scaled, rotated, or moved in the space. The floating model is defined with a datum point whose 3D coordinates indicate the spatial position of the model as the floating mark does. Furthermore, each kind of models is associated with a set of pose parameters to describe its rotation about the three orthogonal axes and shape parameters to describe its scales along predefined directions. In other words, the floating model is a flexible entity floating in the space, and can be adjusted to fit the object by these parameters. If the model parameters are good enough to represent the 3D spatial information of the object, the projection of the floating model on every overlapped image will all be coincident to the object's image. Therefore, the basic idea of the floating model theory is to fit model to the overlapped images by adjusting the model parameters. In order to meet the needs of building reconstruction, we designed several primitive models and established a model-base that is composed of four kinds of models: point, line segment, surface, and solid. By means of human-computer interface, the operator is able to choose the most suitable model and measure the object on multiple images simultaneously. For the building with complicated structure, the extraction can be implemented following the Constructive Solid Geometry(CSG) according to the required level of details. The building can be split into several parts, modeled part-by-part, and finally joined into a complex model by Boolean Set Operators. Based on the floating model theory and model-based building extraction, we proposed a semi-automated extraction strategy. A friendly human-machine interface is designed for the operator to choose and adjust the floating model to fit the images manually. Then, the computer calculate the optimal fit by an ad hoc Least-Squares Model-Image Fitting(LSMIF) algorithm. Thus the 3D spatial information can be extracted object-by-object rather than point-by-point by means of floating model, which increases the efficiency and accuracy. Tested by a series of experiments on real aerial images, the proposed floating model has shown its capability and potential for 3D spatial information extraction.
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