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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 趙鍵哲 | |
dc.contributor.author | Wan-Ting Chen | en |
dc.contributor.author | 陳婉婷 | zh_TW |
dc.date.accessioned | 2021-05-13T06:48:55Z | - |
dc.date.available | 2019-08-25 | |
dc.date.available | 2021-05-13T06:48:55Z | - |
dc.date.copyright | 2017-08-25 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-08-19 | |
dc.identifier.citation | Ackermann, F., 1983. High precision digital image correlation, Proceedings of the 39th photogrammetric Week, University of Stuttgart, pp. 231-243.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/2727 | - |
dc.description.abstract | 隨著電腦設備及攝影測量技術的進步,立體匹配已可有效產製高密度點雲。但是,對於弱紋理區,考量場景或物件地域性、施作條件及硬體需求性,在人工紋理的輔助作業模式下,還有許多限制及作業挑戰待解決。立體匹配藉由投射人工紋理於場景或物件以增加其紋理變化及豐富度,考量場景幾何、大小及所需重建之完整度,會對應不同的方法選擇、設備需求及操作細節。本研究採用一般消費型投影機及相機,在低成本的設備需求下搭配所設計人工紋理、影像拍攝配置、像點量測與方位解算一套流程拍攝影像及獲致品質足夠的方位參數,並利用SURE進行影像密匹配獲取三維點雲。本研究工作具體貢獻主要分為人工紋理設計及取像幾何規劃,人工紋理包括用於影像密匹配的匹配紋理及連接拍攝不同紋理的相鄰像對的連結紋理;由所需的重建精度,可推求攝影測量作業參數包含像主距、物距、像基距及f-number等參數,結合適當的相機與投影機之設備配置以進行影像獲取。本研究從模擬場景的三維重建進行模擬資料與實際資料成果分析,再推展至真實場景之三維重建。本研究提出的人工紋理及設備配置對人工場景及真實場景均可達至預期精度中的三維重建成效。 | zh_TW |
dc.description.abstract | Stereo matching can effectively produce dense point cloud, but it may encounter great challenge when faced with low-textured image content. Even added with artificial texture, the location of the targeted scene, operation condition, and hardware requirement, among others, still demand considerable concerns to arrange for appropriate work scheme. This work captures images by low cost projectors and a camera, and dense matching software SURE is used to generate 3D point clouds. Regarding how and what to project textures, the main focus is on analyzing and designing suitable textures taking the surface, geometry, and making succession of scene into consideration. On the other hand, the fine placements of projectors and camera stations are also crucial to maintaining quality imaging geometry. The four main parameters for image acquisition, baseline, object distance, principal distance, and f-number can be determined by the required accuracy for 3D reconstruction. This study establishes appropriate work steps and rules for reconstructing low texture scene, and the experiments validate its effectiveness and applicability meeting quality requirement. | en |
dc.description.provenance | Made available in DSpace on 2021-05-13T06:48:55Z (GMT). No. of bitstreams: 1 ntu-106-R04521120-1.pdf: 8774093 bytes, checksum: cb93c6f464f68e24526bcdf4e91e6636 (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | 誌謝 I
摘要 II ABSTRACT III 目錄 IV 圖目錄 VII 表目錄 IX 第一章 緒論 1 1.1 前言 1 1.2 研究動機與目的 4 1.3 研究方法與流程 5 1.4 論文架構 6 第二章 文獻回顧 7 2.1 結構光系統 7 2.2 影像密匹配 10 2.3 小結 14 第三章 研究方法 15 3.1 紋理設計 15 3.1.1 匹配紋理 20 3.1.2 連結紋理 22 3.2 攝影規劃 23 3.2.1 計算攝影參數 23 3.2.2 設備配置 26 3.3 像點量測 27 3.3.1 控制點與檢核點像點量測 28 3.3.2 連結點像點量測 28 3.4 方位解算模式 32 3.5 小結 35 第四章 實驗及成果分析 37 4.1 實驗設備與軟體 38 4.2 控制點與檢核點物空間坐標量測 40 4.3 紋理密度 40 4.4 場景1 50 4.4.1 坐標系統 51 4.4.2 影像獲取 51 4.4.3 場景1模擬資料製作及成果分析 55 4.4.4 像點量測 66 4.4.5 方位解算 70 4.4.6 點雲成果與品質評估 71 4.5 場景2 76 4.5.1 坐標系統 77 4.5.2 影像獲取 77 4.5.3 像點量測 84 4.5.4 方位解算 88 4.5.5 點雲成果與品質評估 91 4.6 小結 94 第五章 結論與建議 95 5.1 結論 95 5.2 建議 96 參考文獻 99 附錄一 103 附錄二 107 附錄三 109 | |
dc.language.iso | zh-TW | |
dc.title | 以人工紋理協助弱紋理區影像三維重建 | zh_TW |
dc.title | Using Artificial Texture to Assist 3D Reconstruction of
Low Texture Imagery | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蔡展榮,邱式鴻,莊子毅 | |
dc.subject.keyword | 人工紋理,立體匹配,連結紋理,三維重建, | zh_TW |
dc.subject.keyword | Artificial texture,Stereo matching,Tie texture,3D reconstruction, | en |
dc.relation.page | 110 | |
dc.identifier.doi | 10.6342/NTU201704095 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2017-08-20 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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