未來展望

在未來研究針對辨識率方面，因為本篇論文表情辨識是以黃種人和正常的人臉做 辨識，假如特徵被遮住(瀏海、眼鏡)，那麼可能會辨識不出來，未來可針對此方面再 做進一步研究。由於本系統中，其最難克服的就是光源的影響，光源的強弱會造成特 徵點截取的準確性進而影響辨識率，未來可以針對光源處理進行研究或是前處理特徵 擷取部分採用其他的方法。而在提昇辨識正確率的方面，將特徵點的個數增加或是加 入更多的表情排除資訊或許可以提高一些辨識率。

本論文表情辨識系統，因為是針對靜態影像的表情辨識，並非即時系統，處理的 是單張的影像，如將動態影像看成是一張一張的影像也可使用，因此，可進一步發展 為即時的表情辨識系統。

本論文是以CMAC建立表情特徵模糊集合並以其為基礎，去建構表情辨識系統，

由於沒有特別複雜的數學運算，所以易將演算法轉為硬體實現，且隨著維度的增加可 以減少記憶體的使用量。目前本系統是實現在電腦上，未來可以嘗試將此系統實現於 單晶片上。

參考文獻

[1] P. Ekman and W. V. Friesen, “Constants across cultures in the face and emotion,”

Journal of Personality and Social Psychology, vol. 17, pp. 124-129, 1971.

[2] SONY. [Online]. Available: http://www.sony.co.jp/ July 2008 [date accessed]

[3] Karthigayan M. , Rizon M. , Yaacob S. , Nagarajan R. , “A survey on face emotion recognition and applications” Source: Advances in Modelling and Analysis B, v 50, n 3-4, p 42- 64, 2007

[4] Suprijanto, Sari Linda, Nadhira Vebi, Merthayasa Ign., Farida I.M. ,”Development system for emotion detection based on brain signals and facial images” Source:

Proceedings of World Academy of Science , Engineering and Technology, v 38, p324-331,FEBRUARY 2009 E-ISSN: 20703740

[5] R. Cowie, E. Douglas, N. Tsapatsoulis, G. Vostis, S. Kollias, W. Fellenz and J. G.

Taylor.2001. Emotion Recognition in Human-computer Interaction. In: IEEE Signal Processing Magazine, Band 18 p.32 – 80

[6] N. Esau, L. Kleinjohann, and B. Kleinjohann, “Fuzzy Emotion Recognition in Natural Speech Dialogue,” In IEEE Inter. Workshop on Robots and Human Interactive Communication, pp.317 – 322, Aug. 2005

[7] C. Breazeal, “Emotive qualities in robot speech,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 3, pp.1388- 394, 2001 [8] O.W. Kwon, K.

Chan, J. Hao, T.W. Lee , “Emotion Recognition by Speech Signals,” Eurospeech, pp.125-128,2003.

[9] B. Fasel and J. Luettin, “Automatic facial expression analysis: A survey,” Pattern Recognition, vol. 36, pp. 259-275, Sep. 2003.

[10] M. H. Yang, D.J. Kriegman, and N. Ahuja, “Detecting faces in images: A survey,”

IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 24, no. 1, pp. 34-58, Jan. 2002.

[11] 連國珍著， ＂ 數位影像處理 “，儒林圖書出版社，台北市，6 -1~6 – 9，2001 年 8 月二版三刷。

[12] C.Garcia,G.tzirita, “Face detection using quantized skin color region merging and wavelet packet analysis “, IEEE trans . Multimedia , 1(3):264-277 ,1999

[13] C.Garcia,G.simandiris,G.tzirita ,“A feature-based face detector using wavelet frames”, Proc of Intern , workshop on very low bit coding” , pp . 71-76 ,Athens, October 2001

[14] A.Pentland,B.Moghaddam,T.Starner , ” View-based and modular eigenspaces for face recognition ” , Proc. IEEE Conf. Computer Vision and Pattern Recognition , pp.

84-91,1994

[15] C. C. Chiang, W. K. Tai, M. T. Yang, Y. T. Huang, and C. J. Huang, “A novel method for detecting lips, eyes and faces in real time,” Real-Time Imaging, vol. 9, no.

4, pp. 277-287, Aug. 2008.

[16] K. C. Yow and R. Cipolla, “Feature-based human face detection,” Image and Vision Computing, vol. 15, no. 9, pp. 713-735, 1997.

[17] S. L. Phung, D. Chai, and A. Bouzerdoum, “Skin colour based face detection,” in The 7th Australian and New Zealand Intelligent Information Systems Conf., 2001, pp.

171-176.

[18] R. L. Hsu, M. Abdel-Mottaleb, and A. K. Jain, “Face detection in color images,”

IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.24, no.5, pp.

696-706, 2002.

[19] 楊淳凱（蘇木春 教授指導）， “基於自我組織特徵映射圖之人臉表情辨識＂，國 立中央大學, 資訊工程研究所, 碩士論文, 2008.

[20] G. Yang and T. S. Huang, “Human face detection in complex background,” Pattern Recognition, vol. 27, no. 1, pp. 53-63, 1994.

[21] C. Garcia and G. tzirita, “Face detection using quantized skin color region merging and wavelet packet analysis,“ IEEE Trans. on Multimedia, vol. 1, no. 3, pp.

264-277, September 1999.

[22] Y. Araki, N. Shimada, and Y. Shiral, “Detection of faces of various directions in complex backgrounds,” in Proc. of the 16th IEEE Int. Conf. on Pattern Recognition, Washington, Aug. 2002, vol. 1, pp. 409-412.

[23] A. Lanitis, C. J. Taylor, and T.F. Cootes, “An automatic face identification system using flexible appearance models,” Image and Vision Computing, vol. 13, no. 5, pp.

393-401, 1995.

[24] M.A. Turk and A.P. Pentland, "Face recognition using eigenfaces," presented at Computer Vision and Pattern Recognition, 1991.

[25] J. Yang, D. Zhang, A.F. Frangi, and J.J.Y Yang, ”Two-Dimensional PCA: A New Approach to Representation and Recognition”, IEEE Transactions on pattern analysis and machine intelligence, pp.131-137, 2004.

[26] Christophe Garcia,Manolis Delakis “A neural architecture for fast and robust face detection “，Pattern Recognition, 2002. Proceedings. 16th International Conference on , Volume: 2 , 11-15 , pp. 44-47 ,Aug. 2002

[27] H.A. Rowley, S. Baluja, T.Kanade, “ Neural network-based face detection “, IEEE Trans. Pattern Analysis and Machine Intelligence, vol.20 ,no.1 ,pp. 23-38,Jan.1998

[28] H.A Rowley, S.Baluja, T.Kanade, “ Rotation Invariant neural network-based face detection “, Proc. IEEE Conf. Computer Vision and Pattern Recognition , pp.

38-44,1998

[29] P. Viola and M. J. Jones, “Rapid object detection using a boosted cascade of simple features,” in Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Dec. 2001, vol. 1, pp. 511-518.

[30] E. Osuna, R. Freund and F. Girosi, “ Training support vector machines : an application to face detection,“IEEE Conf. on Computer Vision and Pattern Recognition, pp. 130-136, June 1997.

[31] 謝怡竹（蘇木春 教授指導），“以光流為基礎之自動化表情辨識系統＂，國立中 央大學， 資訊工程研究所， 碩士論文， 2005.

[32] P. Wanga, F. Barrettb, E. Martin, M. Milonova, R. E. Gur, R. C. Gur, C. Kohler, and R. Verma, “Automated video-based facial expression analysis of neuropsychiatric disorders,” Neuroscience Methods, vol. 168, pp.224-238, Feb. 2008.

[33] T. F. Cootes, G. J. Edwards, and C. J. Taylor, “Active appearance models,”IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 681-685, 2001.

[34] N. Esau, E. Wetzel, L. Kleinjohann, and B. Kleinjohann, “Real-time facial expression recognition using a fuzzy emotion model,” in 2007 IEEE Int. Conf. on Fuzzy Systems, July 2007, pp. 1-6.

[35] C. Zhan, W. Li, F. Safaei, and P. Ogunbona, “Emotional states control for on-line game avatars,” in Proc. of the 6th ACM SIGCOMM workshop on Network and system support for games, 2007, pp. 31-36.

[36] P. Viola and M. J. Jones, “Rapid object detection using a boosted cascade of simple features,” in Proc. of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Dec. 2001, vol. 1, pp. 511-518.

[36] P. Ekman and W.V. Friesen, The Facial Action Coding System: A

Technique for The Measurement of Facial Movement. San Francisco: Consulting Psychologists Press, 1978.

[37] 吳明衛（郭淑美 教授指導）， “自動化臉部表情分析系統＂，國立成功大學，

資訊工程系，碩士論文， 2003。

[38] N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines.

Cambridge University Press, 2000.

[39] Chuang Chao-Fa, Shih Frank Y.,” Recognizing facial action units using independent component analysis and support vector machine" Source: Pattern Recognition, v 39, n 9, p 1795-1798, September 2006 ISSN: 00313203

[40]BeszédeŠ Marian, Culverhouse Phil, Oravec Miloš, “Facial emotion classification using active appearance model and support vector machine classifier,” Source:

Machine Graphics and Vision, v 18, n 1, p 21-46, 2009 ISSN: 12300535 [41] S. R. Gunn, 1998, “Support Vector machines for classification and regression,”

Technical Repor,t University of Southampton.

[42] 何明哲 (江政欽 指導教授)， “以模糊推論進行臉部動作元之分析與辨認＂， 國 立東華大學， 資訊工程學系, 碩士論文， 2004。

[43] M. Soriano, S. Huovinen, B. Martinkauppi, and M. Laaksonen, “Using the Skin Locus to Cope with Changing Illumination Conditions in Color-Based Face Tracking,” Proc.

of IEEE Nordic Signal Processing Symposium, pp. 383-386, 2000.

[44] 黃泰祥（繆紹綱教授指導），“具備人臉追蹤與辨識功能的一個智慧型數位監 視系統＂，私立中原大學，電子工程研究所， 碩士論文， 2004.