博碩士論文 983202079 詳細資訊




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姓名 李孟儒(Meng-Ju Lee)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 利用近景影像提高三維建物模型之細緻化等級
(Increase the Level of Detail of 3D Building Models with Close-Range Images)
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摘要(中) 隨著科技進步,視覺模擬與數碼城市的應用越趨廣泛且日新月益,然而,現今數碼城市與三維建物模型應用與展示的內容大都提供使用者進行大範圍的瀏覽與使用,而較少提供比較細緻的物件模擬或瀏覽。本研究以OGC LOD2的建物模型作為基礎,提出有效的方法利用近景影像提高三維建物模型的細緻化等級。本研究所研發的方法利用影像特徵以及實際建築物結構元件之特性為判斷條件,並且配合語義學分析與影像處理技術,有效判釋建物的窗戶、門、陽台等建築結構元件。再利用空間前方交會進行三維定位,以多張影像量測門窗等元件的尺寸,進行附屬物件之重建,達成三維建物模型細緻化,以快速、有效率且準確的完成具有較高細節層級的建築模型。
摘要(英) The development of computer graphics and geospatial technologies lead to the fast progress in Cyber City implementation and applications. Due to the complexity and diversified applications of digital city models, different levels of detail (LOD) may be necessary in order to fulfill different requirements. Currently, popular digital city systems, such as Google Earth or Bing Earth, mostly utilize LOD1 or LOD2 models, most of the applications still focus on large-scale use and low level of detail building models, these may be inadequate for applications in the engineering domain and other fields. This research develops systematic methods and procedures to increase the level of detail of 3D building models using close-range images and based on low level of detail building models. The idea is to refine CityGML LOD2 models with detail facade objects extracted from close-range images to increase the level of detail of 3D building models. The developed algorithms use image features and characteristics of building structure objects in real world with semantic analysis and digital image processing to recognize the structure objects like windows, doors, balconies, etc. The developed algorithms employ digital image processing to establish the rules to recognize the structure objects and building details from close-range images. Dimensions and positions of the objects are also determined . The identified objects are then added onto the LOD2 models to reconstruct high detailed model.
關鍵字(中) ★ 語意分析
★ 細節層級
★ 三維建物模型
關鍵字(英) ★ Level of Detail(LOD)
★ Semantic Analysis
★ 3D Building Model
論文目次 中文摘要 I
ABSTRACT II
致謝 IV
目錄 V
圖目錄 VII
表目錄 XII
第一章 緒論 1
1.1背景介紹 1
1.2研究動機與目的 5
第二章 文獻回顧 9
2.1 邊緣偵測 11
2.2 語意概念 16
2.3語意判釋與分析 17
2.4論文架構 20
第三章 研究方法 22
3.1 研究流程 22
3.2特徵區塊萃取 25
3.2.1 影像幾何校正 26
3.2.2 不規則牆面幾何校正 27
3.2.3 影像特徵萃取 30
3.2.4 區塊合併 33
3.3第三維深度尺寸定位 34
3.3.1 空間前方交會 34
3.4 語意分析與語意模型 38
3.4.1 模型屬性獲取 39
3.4.2 語意分析與語意模型 39
第四章 實驗成果與分析 45
4.1研究資料簡介 45
4.2 案例一:國立中央大學工程五館 46
4.3 案例二:台北市政府 60
4.4 案例三:台北國際會議中心 72
第五章 結論與未來展望 81
參考文獻 86
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指導教授 蔡富安(Fuan Tsai) 審核日期 2011-8-15
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