結合光達資料與大比例尺向量圖重建三維建物模型

Fusion of LIDAR Data and Large-Scale Vector Map for Building Reconstruction

陳良健(Liang-Chien Chen) ； 郭志奕(Chih-Yi Kuo)

《航測及遙測學刊》 11卷4期 (2006/12) Pp. 361-380

https://doi.org/10.6574/JPRS.2006.11(4).2

摘要

數碼城市日益重要。而在數碼城市中，建物為其必要單元。光達資料(LIDAR data)的引進，為自動化建物重建之研究方向帶來可能性。大比例尺向量圖具有精確之二維屋緣線，而光達資料具有豐富之屋頂面資訊。故本研究欲結合以上兩種資料之優勢，進行三維建物重建。本研究工作流程主要分為三部分：(1)資料整合、(2)建物頂共面分析、及(3)建物模塑。在資料整合部分，內容為兩資料之前處理，光達資料需去除地表起伏，而向量圖需建構封閉多邊型。在建物頂共面分析部分，以區塊成長法進行牆面和屋頂面之偵測。最後在建物模塑部分，內容為求取建物三維結構線段，利用SMS法建立結構線位相關係並模塑建物屋頂面高度。本研究並以台中大坑進行測試。光達資料點密度約1.71（點／平方公尺），向量圖比例尺為1:1000，重建完全正確率約90%，模塑誤差為0.17m。

關鍵字

光達資料 ； 向量圖 ； 三維建物重建 ； 迪式三角網

並列摘要

Cyber city is getting important. Building models, among others, could be the most important elements in a cyber city. Due to its maturity, LIDAR data has demonstrated profound potentials in fully automatic building reconstruction. LIDAR data contains plenty of height information, while vector maps preserve accurate building boundaries. From the viewpoint of data fusion, we strive to integrate two data to perform building modeling. The proposed scheme comprises three major steps: (1) preprocessing of LIDAR data and vector maps, (2) segmentation and detection of wall and roof faces, and (3) building modeling. In the preprocessing stage, the height variation of the above-ground objects is determined by subtracting the surface elevation from the terrain. The closed polygons for buildings are also obtained. In next stage, segmentation and detection of wall and roof faces is implemented by region growing. In the step of the building modeling, the construct edges of a building could be obtained. Then the 2D topology of building edges is obtained by SMS method. Finally, building models are reconstructed. The test data covers Tai-Chung city in Taiwan. The average density of LIDAR data is about 1.71 points per square meter. The vector maps are with a scale of 1:1000. About 90% buildings are correctly reconstructed by the proposed method. The shaping error is about 0.17m.

並列關鍵字

LIDAR ； Vector Maps ； Building Reconstruction ； Triangulated Irregular Network