臺灣博碩士論文加值系統

在人臉辨識與人臉驗證的相關研究中，線性鑑別式分析(Linear Discriminant Analysis, LDA)是一種常見的線性轉換技術，透過LDA轉換後可以求出一組具有鑑別性的特徵參數。然而應用在線上的人臉辨識與人臉驗證系統上，必須因應資料的更新與刪除等情況，重新訓練LDA的轉換參數，LDA的轉換參數包括了散佈矩陣與轉換矩陣。傳統的LDA需花相當多的時間才能獲得更新後的轉換參數，在本篇論文中針對傳統LDA無法有效動態更新這些參數的缺點，提出了一個動態LDA演算法，利用代數的運算，不但能節省重新訓練的時間，在重新訓練時也只需要保留少數的相關參數，即能無誤差的獲得更新後的轉換參數。另外在人臉驗證的系統上，藉由 LDA與最佳相似度線性轉換(Maximum Likelihood Linear Transformation, MLLT)的結合獲得最佳的線性轉換矩陣，並且應用機率分布的概念對人臉驗證的問題作假設檢定(Hypothesis Testing)根據相似度比值(Likelihood Ratio, LR)為F分配，選擇不同的顯著水準進行假設檢定。本論文提出驗證的方法優於傳統人臉驗證的方法，主要是因為傳統方法採用相似度比值測試(Likelihood Ratio Test, LRT)，並用經驗法則手動的調整驗證的門檻值(threshold)，本方法可以依照不同的需要，選擇不同的顯著水準進行檢定。實驗中，我們將所提出來的方法應用在中研院人臉資料庫及本實驗室收集的汽車人臉資料庫皆有不錯的效果，我們也實現一套線上動態人臉辨識及驗證展示系統。

Linear Discriminant Analysis (LDA) is a popular linear transformation method for face recognition verification. Using LDA, we can extract the low-dimensional discriminative feature parameter for human faces. In the applications of face recognition and verification, it is usually necessary to enroll the system with new papers and templates. Also, we often need remove the out-of-date persons or templates from the system model. Namely, using the LDA model, the within and between class scatter matrices and the transformation matrices should be recomputed. However, such a recomputation is very time-consuming. To overcome this weakness, a dynamic LDA algorithm is proposed in this paper. Apply this algorithm, we cannot only save a huge amount of computation time but also obtain the updated new parameters with relatively small storage of model parameters. Moreover, in face verification system, we estimate the optimal matrix via by combining the theories of LDA and Maximum Likelihood Linear Transformation (MLLT). We also derive the distribution of likelihood ratio based on MLLT to be the F distribution. Then, the face verification system is carried out via hypothesis testing using different significant levels for F distribution. The advantage of new method is that the verification decision is done according to statistically meaning "significant levels". This superiority is attractive compared to the conventional method using empirical thresholds. In the experiments, we obtain desirable performance using IIS face database and CSIE/NCKU car face database. An online dynamic face recognition and verification demo system is implemented.

摘要
ABSTRACT
第一章緒論6
1.1 研究動機6
1.2 論文主要內容10
1.3 線上人臉辨識暨驗證流程11
第二章系統架構介紹14
2.1 動態人臉偵測14
2.1.1 考慮人臉與背景的關係加快人臉偵測速度14
2.1.2 像素色彩轉換18
2.1.3相似機率計算比對19
2.1.4 取出影像輪廓並二元化、眼睛輪廓特徵判斷19
2.2 小波臉前處理22
2.3 分類原則24
2.3.1 最接近特徵線25
2.3.2最接近特徵平面26
第三章線性鑑別式分析相關研究探討29
3.1 傳統線性鑑別式分析的基本原則29
3.2 改良式線性鑑別式分析33
第四章動態線性鑑別式分析37
4.1新增(Updating)39
4.1.1更新類別內散佈矩陣 39
4.1.2更新類別間散佈矩陣 40
4.2刪除(Downdating)42
4.2.1更新類別內散佈矩陣 42
4.2.2更新類別間散佈矩陣 43
4.3動態線性鑑別式分析演算法44
4.3.1動態更新平均值演算法46
4.3.2動態更新散佈矩陣演算法47
4.3.3時間複雜度分析48
第五章動態線性鑑別式分析於人臉驗證之應用49
5.1 假設檢定簡介49
5.2 貝氏因子於生物驗證上之應用50
5.3 最佳相似度估測與線性鑑別式分析之關係52
5.4 使用假設檢定於人臉驗證57
第六章實驗60
6.1 人臉資料庫介紹60
6.1.1 中研院人臉資料庫60
6.1.2 成功大學資訊工程學系汽車人臉資料庫61
6.2 動態更新線性鑑別式分析之轉換參數實驗62
6.2.1 新增資料庫中既有類別之影像資料62
6.2.2 刪除資料庫中既有類別之影像資料63
6.2.3 新增類別63
6.2.4 刪除類別63
6.3 人臉驗證實驗66
第七章Demo系統73
7.1 靜態人臉驗證展示73
7.2 動態人臉驗證展示75
第八章結論與未來展望79
8.1 結論79
8.2 未來研究方向80
參考文獻82
附錄一 中研院人臉資料庫部分人臉影像89
附錄二 成功大學資訊工程學系汽車人臉部分人臉影像91

[1]P.N. Bellhumeur, J.P. Hespanha, and D.J. Kriegman, "Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection". IEEE Transactions on Pattern Analysis ans Machine Intelligence, Vol.19, no.7, pp711-720, July 1997
[2]S. Bhattacharyya, T. Srikanthan, and Pramod Krishnamurthy, "Ideal GMM parameters & posterior log likelihood for speaker verification", Proceedings of IEEE Signal Processing Society Workshop, pp.471-480, 10-12 Sept. 2001
[3]Chanchal Chatterjee, Zhengjiu Kang, and Vwani P. Roychowdhury, "Algorithms for Accelerated Convergence of Adaptive PCA", IEEE Transactions on Neural Networks, Vol.11, No.2, pp.338-355, March 2000
[4]L. Chen, H. Liao, M. Ko, J. Lin, and G. Yu, "A new LDA-based face recognition system which can solve the small sample size problem", Pattern Recognition, Vol.33, no.10, pp.1713-1726, 2000.
[5]J.T Chien, C.C Wu, " Discriminant waveletfaces and nearest feature decisions for face recognition". IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.1644 -1649, 2002
[6]C. Chatterjee, V.P. Roychowdury, "On self-organizing alogorithms and networks for classseparability". IEEE Transaction on Neural Network, pp.663-678, 1997
[7]Morris H. DeGroot, "Optimal statistical decisions", McGraw-Hill Publishing Company, 1970
[8]K. Etemad, and R. Chellappa, "Discriminant Analysis for Recognition of Human Face Images", J. Opt. Soc. Amer. A, Vol.14, pp.1724-1733, 1997
[9]K. Fukunaga, "Introduction to Statistical Pattern Recognition", Academic Press, second edition, 1991.
[10]Stephen B. Haley, "The Generalized Eigenproblem: Pole-Zero Computation", Proceedings of the IEEE , Vol. 76 ,pp.103-120 , Feb 1988
[11]K. Hiraoka, S. Yoshizawa, K. Hidai, M. Hamahira, H. Mizoguchi, and T. Mishima, "Convergence analysis of online linear discriminant analysis", Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, Vol.3, pp.387-391,24-27 July 2000
[12]K. Hiraoka, K. Hidai, M, Hamahira, M. Mizoguchi, T. Mishima, and S. Yoshizawa, "Successive Learning of Linear Discriminant Analysis: Sanger-type Algorithm". Proc. International Conference on Pattern Recognition, pp.664-667, 2000
[13]Hui Jiang, and Li Deng, "A Bayesian Approach to the Verification Problem: Applications to Speaker Verification", IEEE Transactions on Speech and Audio Processing, Vol.9, No.8, pp.874- 884, November 2001
[14]Hiraoka Kazuyuki, Hamahira Masashi, Hidai Ken-ichi, Mizoguchi Hiroshi, Mishima Taketoshi, and Yoshizawa Shuji, "Fast algorithm for online linear discriminant analysis". IEICE Transactions on Fundamental of Electronics, Communications and Computer Science,Vol.E-A, pp.1431-1441, 2001
[15]Nagendra Kumar, and Andreas G. Andreou, "Heteroscedastic Discriminant Analysis and Reduced Rank HMMs for Improved Speech Recognition", Speech Communication, Vol.26, No.4, pp. 283-297, December 1998
[16]Hyun-Chul Kim, Daijin Kim, and Sung Yang Bang, " A numeral character recognition using the PCA mixture model", Pattern Recognition Letters, Vol. 23, pp.103-111, January, 2002
[17]Hyun-Chul Kim, Daijin Kim, and Sung Yang Bang, "Face recognition using LDA mixture model", Pattern Recognition, 2002. Proceedings. 16th International Conference on, Vol.2, pp.486-489, Aug. 2002
[18]Hyun-Chul Kim, Daijin Kim, and Sung Yang Bang, " Face recognition using the mixture-of-eigenfaces method", Pattern Recognition Letters, Vol. 23, pp.1549-1558, January, 2002
[19]Hyun-Chul Kim, Daijin Kim, and Sung Yang Bang, "Extensions of LDA by PCA mixture model and class-wise features", Pattern Recognition, Vol. 36, pp.1095-1105, May, 2003
[20]W.S. Lee, H.J. Lee, and J.H. Chung, "Wavelet-Based FLD for Face Recognition", Proc. IEEE Midwest Symp. on Circuits and Systems, Lansing MI, pp. 734-737, Aug. 2000
[21]Stan Z. Li, Kap Luk Chan, and Changliang Wang, "Performance Evaluation of the Nearest Feature Line Method in Image Classification and Retrieval", IEEE Transactions on Pattern Analysis and Machine Intelligence,
Vol. 22, No.11, pp.1335-1339, Nov. 2000.
[22]Chih-Pin Liao, Hsien-Jen Lin, Chien-Che Huang and Jen-Tzung Chien, "Multiple human face detection in complex background", Proc. of 2002 Computer Graphics Workshop, Tainan-Taiwan, June 2002.
[23] Hsien-Jen Lin, Chih-Pin Liao, Chien-Yu Hung and Jen-Tzung Chien, "On improving linear discriminant analysis for face recognition with small sample size problem", Proc. of 2002 Symposium on Digital Life and Internet Technologies, Tainan-Taiwan, June 2002.
[24]Ke Liu, Yong-Qing Cheng, and Jing-Yu Yang, "A Generalized Optimal set of Discriminant Vectors", Pattern Recognition, Vol.25, No.7, pp.731-739, 1992
[25]Ke Liu, Yong-Qing Cheng, Jing-Yu Yang, and Xiao Liu, "An Efficient Algorithm for Foley-Sammon Optimal Set of Discriminant Vectors by Algebraic Method", International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Vol.6, No.5, pp.817-829, 1992
[26]C. Liu, and H. Wechsler, "Enhanced Fisher linear discriminant models for face recognition", Proc. of IEEE Int''l conf. on Pattern Recognition, Vol.2, pp.1368 -1372, 1998
[27]Juwei Lu, Konstantinos N. Plataniotis, and Anastasios N. Venetsanopoulos, "Face recognition using kernel direct discriminant analysis algorithms", IEEE Transactions on Neural Networks, Vol.14 ,pp.117-126, Jan. 2003
[28]Juwei Lu, Kostantinos N. Plataniotis, and Anastasios N. Venetsanopoulos, "Face Recognition Using LDA-Based Algorithms", IEEE Transactions on Neural Networks, Vol.14, No.1, pp. 195 -200, January 2003
[29]M.W. Mak, C.K. Li, and X. Li, "Maximum likelihood estimation of elliptical basis function parameters with application to speaker verification", Fourth International Conference on Signal Processing Proceedings, Vol.2, pp.1287-1290, 12-16 Oct. 1998
[30]Aleix M. Martinez, and Avinash C. Kak, "PCA versus LDA", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23,pp.228-233, February 2001
[31]Golfarelli Matteo, Maio Dario, and Malton Davide, "On the error-reject trade-off in biometric verification systems", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.19, pp.786-796, July 1997
[32]E. Oja,"A simplified neruon model as a principal component analyzer". Mathematical Biology, pp.267-273, 1982
[33]Beresford N. Parlett, "The QR Algorithm". IEEE Computational Science and Engineering , Vol. 2, pp.38-42, 2000
[34]J.C Principe, Dongxin Xu, and Chuan Wang, "Generalized Oja''s Rule for Linear Discriminant Analysis with Fisher Criterion". Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing Vol. 4, pp.3401 -3404, Apr 1997
[35]Chellappa Rama, C.L. Wilson, and Sirohey Saan, "Human and machine recognition of faces: a survey", Proceedings of the IEEE , Vol.83, pp.705-741, May 1995
[36]Brunelli Roberto, and Falavigna Daniele, "Person identification using multiple cues", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.17, pp.955-966, Oct. 1995
[37]George Saon, Mukund Padmanabhan, Ramesh Gopinath, and Scott Chen, "Maximum Likelihood Discriminant Feature Space", Acoustics, Speech, and Signal Processing, 2000. ICASSP ''00. Proceedings. 2000 IEEE International Conference on , Vol.2 ,pp.1129-1132, 5-9 June 2000
[38]Wang Song, and Xia Shaowei, "Robust PCA based on neural networks", Proceedings of the 36th IEEE Conference on Decision and Control, Vol.1, pp.503-508, 10-12 Dec. 1997
[39]Roman W. Swiniarski, and Andrzej Skowron, "Rough set methods in feature selection and recognition", Pattern Recognition Letters, Vol.24, pp. 833-849, June 2003
[40]Dian I. Witter, and Michael W. Berry, "Downdating the Latent Semantic Indexing Model for Conceptual Information Retrieval". The Computer Journal Vol. 41, pp.589-601, 1998
[41]Ze Wang, Yin Lee, Simone Fiori, Chi-Sing Leung, and Yi-Sheng Zhu, "An improved sequential method for principal component analysis", Pattern Recognition Letters, Vol.24, pp. 1409-1415, June 2003
[42]Lei Xu, and A.L. Yuille, "Robust principal component analysis by self-organizing rules based on statistical physics approach", IEEE Transactions on Neural Networks, Vol.6, pp.131-143, Jan. 1995
[43]Lei Xu, E. Oja, and Ching Y. Suen, "Modifed hebbian learning for crve and surface fitting". Neural network Vol.5, pp.441-457, 1992
[44]Zonglin Zhou, S.Z. Li, and Kap Luk Chan, "A theoretical justification of nearest feature line method", Pattern Recognition, 2000. Proceedings. 15th International Conference on, Vol.2, pp.759-762, Sept 2000
[45]Jian Yang, and Jing-yu Yang, "Why can LDA be performed in PCA transformed space? ", Pattern Recognition, Vol. 36, pp.563-566, February, 2003
[46] M.-H. Yang, N. Ahuja, and D. Kriegman, "Face recognition using kernel eigenfaces", Proceedings. 2000 International Conference on Image Processing , Vol.1 , pp.37-40,10-13 Sept. 2000
[47]Yiying Zhang, and Xiaoyan Zhu, "A fast speaker verification method with global speaker model", International Conference on Communication Technology Proceedings, Vol.2 , Oct. 1998
[48]吳佳珍, "以鑑別性小波參數為主之人臉辨識研究系統", 國立成功大學資訊工程學系碩士論文, Jun 2001
[49]林咸仁, "改良線性鑑別式分析在少量訓練樣本下之人臉辨識研究", 國立成功大學資訊工程學系碩士論文, July 2002