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  • 學位論文

獲取多方向影像於三維顏面模型重建

A Facial Model Reconstruction with Images Acquired from Multiple Directions

指導教授 : 張哲豪

摘要


隨著電腦快速發展,加上相機解析度不斷提高,如何利用攝影測量技術快速建立高精度三維模型,並提供可視化多角度測量與展示,相較傳統測量做法則可省去大量時間。然而,近景攝影測量技術現今廣泛運到各種領域中,如橋梁監測、邊坡監測、醫療整形等,這些領域對於建立三維模型精度需求不盡相同,但是在醫療整形和外科手術前建立之三維模型,精度要求應至少需達到公釐(mm)等級。石佑偉(2010)使用物空間匹配法已經成功建立高精度顏面三維模型,其精度達到1mm以下。但是前者研究卻少掉耳朵三維空間資訊於全顏面模型上,將造成全顏面特徵標的(Landmark)角度無法測量,本研究從此地方加以改善。 本研究主要分為五部分:(1)改變以往只對臉部正面垂直拍攝,改以多視角方式拍攝。(2)加入相機透鏡畸變差修正至物空間匹配法(Object-Space Matching),並以左側、中間及右側概念建立全顏面三維模型,並與其它不同匹配法比較精度。(3)將產製點雲模型組三角網並敷貼正射影像和點雲模型加入RGB資料等兩種方法展示全顏面模型。(4)使用二維像片測量方法與三維模型測量方法進行10個全顏面特徵標的測量,並作測量精度比對(5)針對30位年齡在19~30歲之成年男女使用三維模型測量方法進行特徵標的測量與統計,測得全顏面線條長度與角度提供日後研究分析之參考。

並列摘要


As the prompt development of IT technology, plus the continuous enhancement of camera resolution, utilizing photogrammetry to establish highly precise 3-dimensional (3D) models becomes more and more popular. Photogrammetry can also provide visible multi-angle measurement and display. Compare with traditional measurement methodology, photogrammetry is a great time saver. However, for different fields of photogrammetry applications such as bridge monitoring, slope monitoring, and plastic surgery … etc, the precision requirements of 3D models are not quite the same. The 3D-models precision requirements for the plastic surgery and surgical operation should at least up to millimeter level. Domestic literature indicates that object-space matching related studies have already successfully established facial 3D models with the precision up to less than 1mm. However, these studies lack of applying ear 3D models to the facial models which will cause failure to establish overall facial landmark. This is the enhance focus for this study. There are 5 parts in this study: (1) change from the past only taking straight facial photos with multi-viewing angles approach; (2) add in the concept of camera lens distortion difference to object-space matching, establish overall facial 3D model with left-side, middle, and right-side view; (3) by adding in two methodologies (product point cloud model set triangular mesh & apply orthophoto and adding in point cloud model to the RGB data) to display facial models; (4) utilizing 2D photogrammetry and 3D model measurement methodology to conduct 10 facial symbol landmarks measurements, and performance the comparison of the precision; (5) in the end of the experiment, will apply this facial symbol landmark 3D measurement to 30 grown ups (aged between 19-30) to establish statistics. The measuring results like overall facial line length and angles can be provided for further analysis and reference in the future.

參考文獻


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被引用紀錄


簡晉翔(2013)。深度資訊輔助多視角合成方法應用於三維人臉辨識與重建〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2013.00825

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