中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/1066
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 80990/80990 (100%)
造訪人次 : 41663880      線上人數 : 1673
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋


    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/1066


    題名: 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
    作者: 郭志奕;Chih-Yi ,KUO
    貢獻者: 土木工程研究所
    關鍵詞: 迪式三角網;三維建物重建;向量圖;光達資料;Triangulated Irregular Network;Vector Maps;Building Reconstruction;LIDAR
    日期: 2005-06-06
    上傳時間: 2009-09-18 17:19:21 (UTC+8)
    出版者: 國立中央大學圖書館
    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,並以整體平差進行建物幾何約制調整。 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。 Cyber city is getting important due to the developments of computer technology and the demands from city management. 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 try to integrate LIDAR data and large-scale vector maps 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 faces and roof faces, and (3) building modeling. In the preprocessing of LIDAR data, 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 faces and roof faces is implemented by region growing. In the step of the building modeling, the construct edges of a building can be obtained. We also implement the geometric constraints by least squares adjustment. The test data covers Tai-Chung city in the middle of Taiwan. The average density of LIDAR data is about 1.71 points per square meter. The vector maps are with a scale of 1:1,000. About 90% buildings are correctly reconstructed by the proposed method. The shaping error is about 0.17m.
    顯示於類別:[土木工程研究所] 博碩士論文

    文件中的檔案:

    檔案 大小格式瀏覽次數


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明