博碩士論文 104323080 詳細資訊




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姓名 任宥霖(You-Lin Ren)  查詢紙本館藏   畢業系所 機械工程學系
論文名稱 基於二維影像輪廓重建三維模型技術之多視角相機群組空間座標系統整合
(The Integration of Coordinate Systems from Multi-View Camera Groups for Shape-From-Silhouette Technique)
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摘要(中) 本研究發展一套多視角相機群組空間座標系統整合的流程。基於輪廓法(Shape-from-Silhouette, SFS)方向進行三維模型重建時,通常會利用旋轉平台輔助拍攝,也因為旋轉平台的緣故,於拍攝欲建模之物件時,其頂部與底部往往會因為資訊獲得不足甚至無法取得,導致於重建三維模型時產生假面,造成三維模型與實際物件外形產生落差。 本研究透過改變物件放置於旋轉盤上的方式,拍攝物件不同角度之影像,以補足物件頂部、底部甚至其他角度特徵之資訊,並利用所有資訊重建三維模型,使其能夠更接近物件之外表形貌。拍攝環境之空間座標系統為透過校正物進行建立,因此改變放置方式進行拍攝之輔助視角資訊必須依附初次拍攝之主要視角所建立的座標系統,故本研究開發一套影像匹配對位法(Alignment by Image Matching, AIM)進行座標系統的整合。藉由計算原始三維模型之投影影像以及輔助視角物件影像之間的空間關係,進而換算各視角相機群組於三維空間中之轉換關係,便可利用更充足之資訊重建三維模型。 本論文最後舉出三個不同的範例,利用本研究提出之多視角相機群組空間座標系統整合流程以及AIM方法,將多組輔助視角的相機群組資訊進行整合,並輸入至應用端進行三維模型的重建,以此驗證本研究之正確性及可行性。
摘要(英) This study develops a process of the integration of coordinate systems from multi-view
camera groups for shape-from-silhouette (SFS) technique. The popular 3D modeling technique
which based on the SFS method usually through the rotatory table to obtain geometry and color
information of object. However, the rotatory table only rotate in one axis, and it causes that the
object has the limitation of the shooting angle especially at the top/bottom view. In SFS method,
this limitation leads the artifacts of 3D model generated at the top/bottom.
If the object can tip over, reposition on the rotatory table, and retake the images, the
missing information of 3D model from top/bottom view could be replenished. In order to
integrate the entire silhouette data taken from different views into a single coordinate system,
this study develops an alignment by image matching (AIM) algorithm to establish the spatial
distribution of all camera positions. In this algorithm, the silhouette data obtained in tipped
positions is setting as targets. The 3D model transforms into a predicted positon to simulate one
of tipped positions and projects the shape onto the imaging plane of the camera to obtain the
predicted silhouette data as a subject. Then, this subject silhouette data will make the
comparison with corresponding target. The AIM algorithm used to minimize the difference
between these two data and calculate the corresponding translation and rotation of the subject
needed to adjust in 3D space. When the sum of differences in all tipped positions is minimum,
all camera position (in auxiliary views) can integrate into a coordinate system of primary view.
A complete 3D model can be rebuilt by the SFS method with all silhouette data in all views.
At last, this study will demonstrate three examples which were rebuilt by the development
of process of the integration of coordinate systems from multi-view camera groups for shapefrom-
silhouette technique to verify our proposed process.
關鍵字(中) ★ 三維建模
★ 逆向工程
★ 最近點迭代
★ 座標系統整合
關鍵字(英) ★ 3D modeling
★ reverse engineering
★ iterative closest points algorithm
★ integration of coordinate systems
論文目次 目錄
1
摘要 ............................................................................................................................................ I
ABSTRACT ............................................................................................................................. II
致謝 ......................................................................................................................................... III
目錄 ......................................................................................................................................... IV
圖目錄 ..................................................................................................................................... VI
表目錄 ..................................................................................................................................... XI
第一章 緒論 .............................................................................................................................. 1
1-1 研究背景 ..................................................................................................................................................... 1
1-2 文獻回顧 ..................................................................................................................................................... 3
1-3 先前成果 ..................................................................................................................................................... 8
1-4 研究動機 ................................................................................................................................................... 11
1-5 研究目的 ................................................................................................................................................... 12
1-6 論文大綱 ................................................................................................................................................... 13
第二章 理論說明 .................................................................................................................... 14
2-1 相機模型 ................................................................................................................................................... 14
2-2 影像處理 ................................................................................................................................................... 19
2-3 邊緣偵測與簡化 ....................................................................................................................................... 23
2-4 奇異值分解 ............................................................................................................................................... 28
2-5 最佳化設計 ............................................................................................................................................... 29
第三章 多視角相機群組空間座標系統整合流程 ................................................................ 36
3-1 流程介紹 ................................................................................................................................................... 37
3-2 影像匹配對位法 ....................................................................................................................................... 40
3-3 相機群組座標系統之建立 ....................................................................................................................... 54
3-4 粗定位流程 ............................................................................................................................................... 57
3-5 精定位流程 ............................................................................................................................................... 68
第四章 結果與驗證 ................................................................................................................ 76
4-1 人機介面與開源資料庫介紹 ................................................................................................................... 76
4-2 範例物件三維模型投影影像驗證 ............................................................................................................ 79
4-3 多視角相機群組資訊重建物件三維模型驗證 ........................................................................................ 92
第五章 結論與未來展望 ...................................................................................................... 106
5-1 結論 ......................................................................................................................................................... 106
5-2 未來展望 ................................................................................................................................................. 107
參考文獻 ................................................................................................................................ 108
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指導教授 廖昭仰 審核日期 2017-10-16
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