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研究生:鄭冠倫
研究生(外文):Guan-Lun Zheng
論文名稱:六個角度頭形影像剪影之立體重建
論文名稱(外文):Silhouette-based 3D Head Model Reconstruction from Six Images
指導教授:張寧群張寧群引用關係
指導教授(外文):Nin-Chun Chang
學位類別:碩士
校院名稱:逢甲大學
系所名稱:自動控制工程所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:68
中文關鍵詞:自動形變極線幾何剪影立體重建
外文關鍵詞:image3D model reconstructionsilhouetteautomatic deformationbaby’s head
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嬰兒頭部模型的立體重建攸關電腦輔助製作嬰兒頭形校正頭盔的成效,在考慮建模方式的安全性及便利性,本論文採用影像重建技術來建模。首先針對取像裝置設計出一台由六個webcam所組成的六角形嬰兒躺床,可分別從嬰兒頭部每隔60度的方向完成同步取像,並依據六張影像中以連續兩張相隔60度影像剪影的立體視覺的極線幾何(Epipolar Geometry)關係及相機校正參數,將兩張所交集區域裡的三維座標求得;在本研究中採用一個通用頭部模型作為參考頭形模型(stl檔案),接著計算參考頭形模型中各三角形網格的面積,並且搜尋相同向量的點,由中心點往外找十三圈網格並配合面積的權重,進行自動變形處理,最後利用B-Spline做平滑化處理。
為驗證實體頭形與電腦重建的差異,本論文使用六個角度由頭頂向下間隔每公分的兩點長度方法比對真實頭形與虛擬頭形。結果顯示真實頭形與虛擬頭形的尺寸比對誤差值誤差在-0.66公分至0.392公分之內,因此在精確度上尚待改進。
The reconstruct of a baby head model is a key factor for producing baby head adjustment helmet. Considering the safety and convenience modeling ways, we use image reconstruction technique to make the model. First, we set up a platform for capturing images that is formed by six webcams to image capture from baby’s head in each 60° , and according to two silhouette by stereo vision and epipolar geometry to get a 3-demensional coordinates; In this research, we take a standard baby head model as a reference head model (stl file), next we calculates each the area of triangle mesh of the reference head model, and search the points that have the same vector, from center to the outside we find 13 layer meshes and to match up with weighting of area, to proceed a automatic deformation processing. Finally, we use B-Spline to perform a smooth processing.
In order to prove the difference between the actual shape of head and the computer reconstruction, we use six angles from head to bottom and one centimeter each two points to compare the actual shape of head and the virtual shape of head. The result shows that the deviation value is between -0.66 cm to 0.392 cm, so there is still a improvement on the accuracy.
致謝 i
摘要 ii
Abstract iii
圖目錄 vi
表目錄 ix
第一章 緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 文獻回顧 8
第二章 研究方法與理論 22
2.1 立體視覺 22
2.2 座標轉換 23
2.3 極線幾何與必要矩陣 25
2.3.1極線幾何 25
2.3.2 必要矩陣 27
2.4 Bresenham’s Algorithm(DDA) 29
2.5 二元樹排序法 (BST Sort) 30
2.6 B-Spline 32
第三章 實驗方法與架構 34
3.1 取向環境評估與建置 35
3.2 camera 校正 39
3.3 影像擷取 44
3.4 影像處理 47
3.5 Visual hull重建 47
3.6 網格變形 52
第四章 實驗結果與討論 56
4.1 結果討論 63
第五章 未來方向 64
參考文獻 65
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