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姓名 姜志宏(Zhi-Hong Jiang) 查詢紙本館藏 畢業系所 機械工程學系 論文名稱 人臉辨識視覺系統之研究 相關論文 檔案 [Endnote RIS 格式] [Bibtex 格式] [相關文章] [文章引用] [完整記錄] [館藏目錄] 至系統瀏覽論文 ( 永不開放) 摘要(中) 在現今的社會中,身份辨識系統在許多場合一直是常見的應用,而人臉是人類對於身份的最基本判定方法,但是電腦要像人類一樣分出誰是誰,目前而言仍然是項挑戰,不同於以往人臉辨識的研究只是根據人臉的二維資訊做探討,本論文根據影像深度和灰階的關系(Shape from shading 簡稱SFS)配合人臉網格,找出人臉上特徵點的三維資訊,依此設計一套簡單的人臉視覺辨識系統。
在實驗上,取得三維資訊的方法是先由人臉正面影像取得129個特徵點,並建立成二維的迪氐三角網格(Delaunay Triangulation),再利用所建立的網格簡化SFS的計算求出所以特徵點的深度值,再依據所求得的特徵點三維資訊和預先建立的資料庫做比對,簡單的利用歐氏距離 (Euclidean Distance)和漢明距離 (Hamming Distance),分辨出輸入的資料是否為資料庫內的成員並分辨其身份。
本研究共收集22位受測者的資料,其中20組資料建立為資料庫,另外2組資料做為測試外來人士的輸入,分別測試後,本系統都可以分辨出輸入資料的身份或判定是否為外來人士。關鍵字(中) ★ 迪氏三角網格
★ 人臉辨識關鍵字(英) ★ SFS 論文目次 摘要.....................................................Ⅰ
致謝.....................................................Ⅱ
目錄.....................................................Ⅲ
圖目錄...................................................Ⅴ
第一章 緒論..............................................1
1.1 研究動機.............................................1
1.2 研究背景.............................................2
1.3 研究目的.............................................3
1.4 論文大網.............................................4
第二章 人臉網格建立......................................5
2.1 迪氏三角網格.........................................5
2.2 Watson演算法.........................................8
2.3 人臉特徵點及網格建立................................10
第三章 影像深度與灰階關系...............................12
3.1 Lambertian餘弦定理..................................12
3.2 利用網格簡化SFS的計算...............................14
3.3 網格端點之Z值求取...................................18
3.4 人臉深度走勢........................................21
第四章 實驗結果.........................................24
4.1 實驗設備及設置......................................24
4.2 人臉辨識系統流程....................................27
4.3 人臉三維模型建立結果................................29
4.4 人臉辨識結果........................................35
第五章 結論及未來展望...................................43
5.1 結論................................................43
5.2 未來展望............................................43
參考文獻................................................45參考文獻 [1] X. Jia and M. S. Nixon, "Extending the feature vector for automatic face recognition", in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17 Issue. 12, pp. 1167–1176, Dec. 1995.
[2] I. J. Cox, J. Ghosn and P. N. Yianilos, "Feature-based face recognition using mixture-distance", in Proc. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recognition, pp. 209–216, 1996.
[3] K. Nagao, "Face recognition by distribution specific feature extraction", in IEEE Conference on Computer Vision and Pattern Recognition, Proceedings, Vol.1, pp.278-285, 2000.
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[8] B. K. P. Horn, "Shape from Shading: A Method for Obtaining the Shape of a Smooth Opaque Object from One View. " in PhD. Thesis, Department of Electrical Engineering, MIT. 1970.
[9] R. Elisabeth and A. Tourin, "A viscosity solutions approach to shape-from-shading", in SIAM Journal on Numerical Analysis ,Vol. 29,Issue. 3,pp.887-884,1992.
[10] V. A. Kovalevsky, "A new approach to shape from shading" In F. Solina, W. G. Kropatsch, R. Klette, R. Bajcsy, : Advances in Computer Vision.
"Advances in Computer Science" Springer Wien New York pp. 159-167, 1997.
[11] N. A. Golias and R. W. Dutton, "Delaunay triangulation and 3D adaptive mesh generation", in Finite Elements in Analysis and Design, Vol. 25, pp. 331-341, 1997.
[12] D. F. Watson, "Computing the n-dimensional Delaunay tessellation with application to Voronoi polytypes", in Computer Journal, Vol. 24, pp. 167-172, 1981.
[13] 林群雄, "基於三角幾何學及顏色特徵作人臉偵測、人臉角度分類與人臉辨識", 國立中央大學資訊工程所博士畢業論文, 2001.
[14] 蘇哲彬, "包含明暗梯度以建立三維物體外形的演算法則", 國立台灣科技大學電機工程研究所碩士畢業論文, 1995.
[15] R. Jain , R. Kasturi and B. G. Schunck, "Machine Vision", International Editions,1995.指導教授 黃衍任(Yean-Ren Hwang) 審核日期 2005-7-19 推文 facebook plurk twitter funp google live udn HD myshare reddit netvibes friend youpush delicious baidu 網路書籤 Google bookmarks del.icio.us hemidemi myshare