人臉三維取像與辨識

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姓名

邱俐雯(Li-Wen Chiu) 查詢紙本館藏

畢業系所

光電科學與工程學系

論文名稱

人臉三維取像與辨識
(Study of 3D Human Face Imaging and Identification)

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摘要(中)

對於現今的量測技術，由於條紋投影輪廓儀 (Projected Fringe Profilometry，PFP) 具有非接觸式的特色，目前被廣泛使用於量測物體三維形貌，本論文即利用條紋投影輪廓儀中的傅立葉輪廓術(Fourier transform profilometry，FTP) 重建物體的三維形貌，其優點具有快速、精準度高且只需單一影像即可還原物體三維形貌。本實驗運用FTP於人臉輪廓上的還原，並在重建的人臉三維形貌上擷取特徵值，利用每個人特徵值具有差異性的特性，提出雙重辨識方法達到辨識的效果。
但在實際拍攝時，人臉會因為傾斜與操作距離不同而產生計算之誤差，透過兩種傾斜修正方法將人臉正規化，並利用三角測距法推算出實際距離，使本系統具有小角度傾斜容忍度以及35~55公分的拍攝容許距離。
我們將人臉資料庫中的85人相互比對，總共比對3570次，藉由雙重辨識方法辨識，辨識率高達99.91%。

摘要(英)

Because of fringe projection profilometry (PFP) has the advantages of non-contact measuring method, and it is widely use for measuring the three-dimensional shape of objects now. In this study, using Fourier transform profilometry (FTP) to reconstruct the three-dimensional shape of an object, which has the advantages of fast, high accuracy and only a single image that can restore the three-dimensional shape of an object. So we use FTP to restore three-dimensional shape of human face and get the feature value from it. Because of each person has unique feature, we proposed the method for double-identification to identification.
In the measuring process, there are some artificial errors which are occurred by human face tilting and shifting. To solve this problem, we proposed two kinds of tilt-correction methods to normalize each human face, and calculating actual distance by using optical triangulation. So that, it allows a small tilt angle tolerance for system and extend shooting distance to 35~55 centimeters. Finally, we compare 85 persons with each other from face database, a total of comparison is 3570 times. By using double-identification method to identify 85 persons for each other, the recognition rate reaches 99.91%.

關鍵字(中)

★ 人臉辨識
★ 條紋投影輪廓儀
★ 傅立業輪廓術
★ 重建
★ 三維形貌

關鍵字(英)

★ face recognition
★ Projected Fringe Profilometry
★ Fourier transform profilometry
★ reconstruct
★ three-dimensional shape

論文目次

摘要 I
Abstract II
致謝 IV
目錄 V
表目錄 XI
第一章緒論 1
1.1背景與發展 1
1.2 條紋投影輪廓儀發展 5
1.3 研究動機 6
1.4 論文大綱與安排 7
第二章實驗基本原理 8
2.1條紋投影輪廓儀基本原理 8
2.1.1 光學三角量測法 9
2.1.2 快速傅立葉轉換原理 12
2.2 相位展開演算法 16
2.3 三角測距法 22
第三章人臉輪廓的建立與特徵值的選取 25
3.1 實驗量測架構 25
3.2 人臉輪廓的建立 27
3.3 系統理論精準度與實際量測結果比較 35
3.4特徵點的選擇與量測 40
3.5 結論 41
第四章人臉辨識與分析 43
4.1人臉傾斜的修正 43
4.1.1 方法ㄧ – 額頭線方程修正法 44
4.1.2 方法二 – 額頭區域性修正法 54
4.2 特徵值的量測 58
4.3 人臉的分析與辨識 59
4.3.1 閥值的設定與辨識 59
4.3.2 系統傾斜容忍度 73
4.4 不同距離的修正 77
4.4.1 定位點的選擇 78
4.4.2 不同距離的判定與分析 80
4.5結論 83
第五章結論 84
參考文獻 86
中英文對照表 91

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指導教授

孫慶成(Ching-Cherng Sun)

審核日期

2016-8-29

推文