結合多元資料重建三維房屋模型; Integrating Multi-source Data for the Generation of 3D Building Models

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题名:	結合多元資料重建三維房屋模型;Integrating Multi-source Data for the Generation of 3D Building Models
作者:	李唐宇;Tang-yu Li
贡献者:	土木工程研究所
关键词:	建物模型;航照影像;光達;向量圖;建物重建;LIDAR;building model;building reconstruction;2D map;aerial image
日期:	2007-06-06
上传时间:	2009-09-18 17:23:39 (UTC+8)
出版者:	國立中央大學圖書館
摘要:	數碼城市可為都市規劃、建設以及管理提供重要的決策資訊。三維建物模型的建立在數碼城市中是不可或缺的。本研究以資訊融合的方式，結合向量圖、光達以及航照資料，重建三維建物模型。重建的重點包括平頂、山型和圓弧頂之建物。研究以向量圖獲取房屋輪廓，因此研究重點為房屋模型之重建。由於圓弧頂之房屋在影像上並無明顯特徵，因此研究用光達之三維資訊來描述圓弧屋頂。為了彌補光達點雲密度可能不足之情形，研究使用航照影像獲取房屋內部結構線。研究中，首先，對三種資料分別進行前處理的作業，接著將房屋內部之光達點雲，由不同的面方程式進行擬合，分出不同屋頂類型。研究中以面方程式描述圓弧頂建物，非圓弧頂者，山型屋將以面相交方式找出屋脊線。平頂屋部份結合光達和航照影像偵測階梯線。最後利用分割-合併-模塑方法模塑產生建物模型。本研究測試區位於新竹科學園區。向量圖比例尺為1：1000，光達點雲密度為1.5點/m2，航照影像之空間解析力為12 cm。研究成果顯示，屋頂面分類成功率可達80%，模型重建正確率為85%。建物輪廓部分均方根誤差在X 方向為0.51 m，Y方向為0.41 m。模塑誤差為0.19 m。 Cyber city provides important information for the city planning, construction, and management. Three dimensional building models are the indispensable component in the cyber city. This investigation integrates 2D maps, LIDAR data, and aerial images for building modeling. This research handles flat, gable, and cambered roofs. Vector maps are used to locate the building boundaries. Since a cambered roof does not have significant features in the image space, we use the LIDAR point clouds to model it. Because the density of the LIDAR point clouds might not be sufficient to reconstruct the internal facets of buildings, we employ aerial images. In the first step, the data preprocessing encloses the polylines of the maps then extract the point clouds that belong to a building. After filtering the point clouds, we fit the data by different surface functions. Through the roof hypothesis by employing point clouds, the camber roofs are parameterized. For non-camber roofs, the ridges of gable roofs will be intercepted by the two inclined planes. The step-edges of flat roofs are obtained by combining point clouds and image features. Then the lines are projected to the object space by ray-tracing. Finally, we shape the models by SMS method. The test site is in the Industrial Technology Research Institute of Hsin-chu. The vector maps are with a scale of 1:1,000. The point density of LIDAR data is 1.5(point/m2), and the spatial resolution of aerial image is 12 cm. The result indicates the successful rate is 80% in building classification while the fully reconstruction rate is 85%. The RMSE of building boundaries are 0.51 m and 0.41 m in X and Y directions, respectively. The shaping error is 0.19 m.
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