(54.236.62.49) 您好!臺灣時間:2021/03/08 03:22
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:李兆智
研究生(外文):Jao-Ji Lee
論文名稱:使用橫向分割的方法進行人臉檢測
論文名稱(外文):Face Detection Using Horizontally Divided Strips
指導教授:李嘉晃李嘉晃引用關係
指導教授(外文):Chia-Hoang Lee
學位類別:碩士
校院名稱:國立交通大學
系所名稱:資訊科學系
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:1999
畢業學年度:87
語文別:中文
論文頁數:40
中文關鍵詞:人臉檢測邊緣檢測人臉特徵人臉幾何結構
外文關鍵詞:face detectionedge detectionfacial featureface geometrical modelHough transform
相關次數:
  • 被引用被引用:2
  • 點閱點閱:116
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
人臉檢測的方法相當多樣化,不論是使用向量的方式來計算或是用類神經網路的方法來訓練,都會有非常大的計算量,而在一些需要 "即時" 的應用上,例如門禁系統的身份辨認,如果要花太久的時間來等待,使用者一定會認為這個系統不甚方便。
本論文試圖以較為直覺的方法來進行人臉檢測的工作。以邊緣檢測為基礎,將圖片予以橫向分割成帶狀長條,便於找出具有邊緣性質的區域範圍,其次使用樣版比對的方式來找出臉的重要特徵--眼睛--的可能位置,然後再根據人臉幾何結構原則找出最可能的具有配對關係的眼睛位置,最後以 Hough 轉換來求得眼睛虹膜的中心。而嘴巴的定位則以眼睛為基準,在符合人臉的幾何結構原則下,來尋找嘴角的定位與嘴唇的外緣。
There are several methods for face detection. No matter using eigenface-based method or neuro network-based training, it usually spend a lot of time on calculating. In some applications need "real time" reaction, if someone have to wait for a long time, he will think that the application is not convenient.
We propose a simple method for face detection. The method is based on edge detection followed by dividing the result map after edge detecting into several horizontal strips. In each strip, we can find some blocks with obvious edges. We call the blocks with interested blocks. Then, using iris template to compare everywhere in interested blocks to find iris candidates. With face geometrical model, we can find some pairs of the iris candidates. Then, applying Hough transform on the pairs to find the centers of iris. With the centers of iris, we have a baseline to decide the range of mouth. After that, we can find the location of mouth and its outline.
中 文 摘 要i
英 文 摘 要ii
致 謝iii
目 錄iv
圖 目 錄vi
第一章 導論1
1.1 人臉檢測與人臉辨識1
1.2 人臉檢測的限制2
1.3 現有人臉檢測方法概觀2
1.3.1 Template Matching Method3
1.3.2 Neural Network-based Method4
1.3.3 Eigenface Method5
1.3.4 Geometrical Model based Method8
1.4 本論文的方法概述10
1.5 論文架構10
第二章 理論基礎與系統概觀11
2.1 理論基礎11
2.1.1 臉的幾何模型11
2.1.2 邊緣檢測13
2.1.2.1 梯度運算子 (Gradient operator)14
2.1.2.2 Prewitt運算子15
2.1.2.3 Sobel運算子16
2.1.2.4 二階導數Laplacian 運算子16
2.1.2.5 各運算子所產生的結果17
2.2 系統概觀18
第三章 眼睛檢測的詳細步驟20
3.1 邊緣檢測20
3.2 尋找梯度值高的區域21
3.3 虹膜的樣版比對22
3.4 找出可能的配對24
3.5 配對的分群25
3.6 用 Hough transform 尋找虹膜中心26
第四章 嘴的檢測的步驟29
4.1 決定嘴的範圍29
4.2 嘴角的檢測30
4.3 檢測上下唇外緣31
第五章 實驗結果與討論33
5.1 實驗的過程討論33
5.1.1 邊緣檢測部分33
5.1.2 將圖形分割成長條狀部分34
5.1.3 虹膜樣版的比對部分35
5.1.4 尋找可能的眼睛配對部分35
5.2 人臉檢測的結果36
5.3 影響檢測的因素探討37
5.4 未來的研究方向38
參考文獻39
[1] Weimin Huang; Qibin Sun; Chian-Prong Lam; Jian-Kang Wu. A robust approach to face and eyes detection from images with cluttered background .
Proc. 14th Intl. Conf. on Pattern Recognition, Vol.1,pp.110 -113,1998.
[2] Kin-Man Lam. A fast approach for detecting human faces in a complex background,
ISCAS ''98. Proc. of the 1998 IEEE Intl. Symposium on Circuits and Systems,
Vol.4,pp.85 -88,1998.
[3] Turk, M.A.; Pentland, A.P., Face recognition using eigenfaces. Proc. CVPR ''91.,
IEEE Computer Society Conference on CVPR, pp.586 -591, 1991.
[4] Sobottka, K.; Pitas, I. A novel method for automatic face segmentation, facial
feature extraction and tracking, Image Communication Signal Processing, Vol.12,
Issue 3, pp.209-286, June 1998
[5] Sun, Q.B.; Huang, W.M.; Wu, J.K. Face detection based on color and local
symmetry information. Proc. Third IEEE Intl. Conf. on Automatic Face and
Gesture Recognition, pp.130 -135, 1998.
[6] Jeng, S.-H.; Hong, Y.M.L.; Chin, C.H.; Ming, Y.C.; Yao, T.L. Facial feature
detection using geometrical face model: an efficient approach.Pattern Recognition,
Vol.31, Issue 3, pp.219-344, pp.273-282, March 1998
[7] Young Ho Kwon; da Vitoria Lobo, N. Face detection using templates,
Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the
12th IAPR Intl. Conf. on Pattern Recognition, Vol.1,pp. 764 -767, 1994.
[8] Rowley, H.A.; Baluja, S.; Kanade, T. Neural network-based face detection . Proc.
CVPR ''96, 1996 IEEE Computer Society Conference on CVPR, pp.203 -208,
1996.
[9] Rafael C. Gonzalez, Richard E. Woods, Digital image processing, Addison
Wesley,1993
[10] Yang, G.; Huang, T.S. Human face detection in a scene. Proc. CVPR ''93., 1993
IEEE Computer Society Conference on CVPR, pp.453 -458, 1993.
[11] Reisfeld, D.; Yeshurun, Y., Robust detection of facial features by generalized
symmetry, Vol.1. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR Intl. Conf. on Pattern Recognition, pp.117 -120, 1992.
[12] Kin Choong Yow; Cipolla, R. Detection of human faces under scale, orientation
and viewpoint variations., Proc. of the 2nd Intl. Conf. on Automatic Face and
Gesture Recognition, pp.295 -300, 1996.
[13] Sung, K.-K.; Poggio, T. Example-based learning for view-based human face
detection., IEEE Trans. on Pattern Analysis and Machine Intelligence,Vol. 20,
pp. 39 -51
[14] Kin Choong Yow; Cipolla, R. A probabilistic framework for perceptual grouping
of features for human face detection. Proc. of the 2nd Intl. Conf. on Automatic Face
and Gesture Recognition, pp.16 -21, 1996.
[15] Qian Chen; Haiyuan Wu; Yachida, M., Face detection by fuzzy pattern matching.
Proc. Fifth Intl. Conf. on Computer Vision, pp.591 -596 , 1995.
[16] Yokoyama, T.; Yagi, Y.; Yachida, M., Facial contour extraction model. Proc. Third
IEEE Intl. Conf. on Automatic Face and Gesture Recognition, pp.254 -259, 1998.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔