多重航照影像之線段匹配於房屋模型重建; Line Matching from Multiple Aerial Images for Building Reconstruction

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题名:	多重航照影像之線段匹配於房屋模型重建;Line Matching from Multiple Aerial Images for Building Reconstruction
作者:	顏柔矞;Yen,Jou-yu
贡献者:	土木工程學系
关键词:	多重航照影像;雙視窗匹配法;線段前方交會;錯誤偵測;房屋模型重建;Multiple aerial images;Left-right matching;Space line intersection;Blunder detection;Building model reconstruction
日期:	2013-07-22
上传时间:	2013-08-22 11:37:05 (UTC+8)
出版者:	國立中央大學
摘要:	近年來，三維資料被廣泛地發展及應用於空間資訊領域。建立三維空間資訊系統的元件有房屋、道路、公共設施、植物等，其中又以房屋模型的重建為最外顯者。重建房屋模型常使用的資料來源之一為航照影像。在多數的房屋樣式中，其邊界處常具有直線特徵結構，因此線段匹配對於房屋模型的重建尤為重要。本研究將藉由高重疊率的航照影像，配合影像線特徵的匹配進行房屋模型之重建。本研究將模型重建分為兩個部分：(1)房屋輪廓重建以及(2)屋頂結構重建。若先建立出房屋的明確輪廓，則後續處理僅需針對屋頂上之附屬結構物，可降低非目標建物的特徵線所造成的影響。此兩部分在基本的處理程序上相似但參數設定上各有考量。首先，使用特徵萃取獲得影像上的直線特徵。接著，利用線段匹配搭配雙視窗的策略找出影像間的共軛線段。於三維線段定位中，線段的前方交會配合錯誤偵測以剔除不可靠的線段，提升交會之品質。最後則以迭代步驟精化初始模型。在房屋輪廓重建時，因處理對象包含非目標房屋的部分，因此需配合興趣線段的選取，剔除非目標房屋之特徵線段。在屋頂結構重建時，其處理之範圍係經由房屋輪廓模型反投影所產生工作區域，區域內的所有線段都可能為重建之目標線段，因此不需額外選取興趣線段。當屋頂結構之三維線段定位完成後，與已建立的房屋輪廓模型整合進行初始模型建立及模型精化，產生最終三維房屋模型。由實驗成果顯示，多張影像的線段匹配能有效提升匹配成功率及正確率。配合錯誤偵測對於三維線段之定位及後續模型之重建品質有顯著的改善。房屋模型之平面誤差約為0.1m，高程則為0.5m左右。 Nowadays, three dimensional data has been widely used in the field of geospatial information. To reconstruct 3D GIS, major components include buildings, roads, utilities, vegetation, etc. Among those components, building models are the most prominent in the reconstruction work. Aerial images are commonly used in building reconstruction. In most of man-made scenes, line segment features usually exist along boundaries. Thus, line matching plays an important role in the building reconstruction. The building reconstruction with line matching algorithm is performed using high overlapping aerial images in this study. The proposed method includes (1) boundary determination and (2) roof structure reconstruction. If the building boundaries can be determined, then the roof structures can thus be processed and the interference of non-target objects can also be reduced. The basic procedures in those two parts are similar with the differences of parameter settings. First, feature extraction is to extract the straight lines, and then use line matching with the strategy of left-right windows to locate the conjugate lines in multiple images. In the 3D line positioning, space line intersection with the blunder detection are combined to derive quality results. The reconstruction and refinement processes are done in an iterative way. In the boundary determination, for the reason that area of interest includes non-target objects, the interest line selection is needed for the estimation of their features. In the roof structure reconstruction, the areas of interest are produced by the back-project of the building boundaries. All of the extracted lines are selected in this stage to avoid line missing. After the 3D line positioning of the roof structure, the boundary model and roof structure are integrated with the initial model reconstruction and refinement to generate the 3D building model. The experimental results indicate that multi-angle images can improve the matching successful rate. With the blunder detection, unreliable matched line segment can be eliminated effectively. The RMSE of the test models can reach 0.1m in X and Y direction, and 0.5m in Z direction.
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