近年來，影像辨識技術隨著電腦運算速度的提昇，其運用也越來越廣泛，尤其以電腦視覺相關的研究為最，而在以往的相關研究中多以靜止的攝影機、單純的背景來做追蹤。本論文以白平衡為輔助搭配影像處理技術，以及自製動態攝影平台作臉部追蹤與辨識的研究。
在人物頭部追蹤的方面，我們利用色彩空間的轉換，以YCbCr為膚色的判定依據，來將膚色從複雜的背景中分離出來，再配合橢圓遮罩搜尋法，找出人臉的所在區域並加以運算及追蹤。經實驗結果證實，本研究提出之人臉追蹤與辨識系統可以有效地尋找出畫面中的人物頭部的區域並標定其中心位置追蹤目標物。

In recent years, image recognition technology is improved by the increasing speed of computer computing and it had more and more applications. Especially, Computer vision related researches are the most popular. The past researches used still camera and pure background to track. This thesis uses image processing technology with assistant white balance and self-made dynamic photographic platform to do face tracking and recognition.
As for human head tracking part, we use color space conversion. YCbCr is the decisive basis for complexion and complexion can be separated from complicated background. With the help of elliptic masking, human face can be located, computed, and traced.
Verified by the experimental result, this study about face tracking and recognition system can efficiently locate human head area and mark its central position to track object.

〔1〕R. Polana and R. Nelson, “Low level recognition of human motion,” in Proc. IEEE Workshop Motion of Non-Rigid and Articulated Objects, pp. 77–82, Austin, 1994.
〔2〕C. A. Pau and A. Barber, “Traffic sensor using a color vision method,” in Proc. SPIE—Transportation Sensors and Controls: Collision Avoidance, Traffic Management, and ITS, vol. 2902, pp. 156–165, 1996.
〔3〕D.-S. Jang and H.-I. Choi, “Active models for tracking moving objects,” Pattern Recognit, vol. 33, no. 7, pp. 1135–1146, 2000.
〔4〕 B. Ugur Toreyin, Yigithan Dedeoglu, Ugur Gudukbay and A. Enis Cetin, “Computer Vision-based Method for Real-time Fire and Flame Detection,” Department of Electrical and Electronics Engineering, August 2005.
〔5〕Rein-Lien Hsu, Anil K Jain and Mohamed Abdel-Mottaleb, “Face Detection In Color Images,” IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol.24,No.5, May 2002.
〔6〕Stan Birchfield, “An Elliptical Head Tracker,” Computer Science Department Stanford University.
〔7〕Stan Birchfield, “Elliptical Head Tracking Using Intensity Gradients and Color Histograms,” Computer Science Department Stanford University.
〔8〕 Yokoo, Y. and M. Hagiwara, “Human faces detection method using genetic algorithm,” in Proc. of IEEE Intl. Conf., Evolutionary Comp., pp.113-118, 1996.
〔9〕Berbar, M. A., H. M. Kelash, and A. A. Kandeel, “Faces and facial features detection in color images,” Geometric Modeling and Imaging -New Trends, vol., issue, pp.209-214, July 2006.
〔10〕Chai, D. and K. N. Ngan, “Face segmentation using skin-color map in videophone applications,” IEEE Trans. on Circuits and Systems for Video Technology, vol.9, no.4, pp.551-564, June 1999.
〔11〕Deng, Y.-C., Vision-based Approaches for Face Recognition, Inst. of Elec. and Cont. Engineering, National Central Univ., Master Thesis, 2001.
〔12〕Garcia, C. and G. Tziritas, “Face detection using quantized skin color regions merging and wavelet packet analysis,” IEEE Trans. on Multimedia, vol.1, no.3, pp.264-277, Sep. 1999.
〔13〕Hsu, R.-L., M. A. Mottaleb, and A. K. Jain, “Face detection in color images,” IEEE Trans. Pattern Anal. Mach. Intell., vol.24, no.5, pp.696-706, 2002.
〔14〕Siana, L., A Study of Human Tracking and Face Detection on A Pantilt-zoom Camera, Inst. of Electrical and Control Engineering National Chiao-Tung Univ., Master Thesis, 2005.
〔15〕Lu, M.-L., Reconstructing Frontal-view Face Image using 3D Computer Graphic Technique, Inst. of Electrical and Control Engineering, National Chiao-Tung Univ., Master Thesis, 2003.
〔16〕陳鴻興, 陳君彥譯, “基礎色彩再現工程＂, 全華科技圖書股份有限公司, 2004。
〔17〕A. Barnard, V. Cardei, and B. Funt, “A Comparison of Computational Color Constancy Algorithms - Part I : Methodology and Experiments with Synthesized Data,” IEEE Trans. on Image Processing, Vol. 11, No. 9, pp. 972-983, 2002.。
〔18〕A. Barnard, V. Cardei, and B. Funt, “A Comparison of Computational Color Constancy Algorithms - Part II : Experiments with Image Data,” IEEE Trans. on Image Processing, Vol. 11, No. 9, pp. 985-995, 2002.。
〔19〕Soriano, M., B. Martinkauppi, S. Huovinen, and M. Laaksonen, “Usingthe skin locus to cope with changing illumination conditions incolor-based face tracking,” in Proc. IEEE Nordic Signal Proc. Symp.,Kolmarden, Sweden, pp.383-386, July 13-15, 2000.
〔20〕Ni, F.-C., Combining PCA and Gray Theory in Human Face Recognition System, Inst. of Electrical and Control Engineering, National Chiao-Tung Univ., Master Thesis, 2002.
〔21〕CCIR, “Encoding parameters of digital television for studios”, CCIR Recommendation 601-2, Int. Radio Consult. Committee, Geneva, Switzerland, 1990.
〔22〕Hu, M., S. Worrall, A. Sadka, and A. Kondoz, “Face feature detection and model design for 2D scalable model-based video coding,” in Proc. Intl. Conf. on VIE, pp.125-128, July 7-9, 2003.
〔23〕Chai, D. and K. N. Ngan, “Face segmentation using skin-color map in videophone applications,” IEEE Trans. on Circuits and Systems for Video Technology, vol.9, no.4, pp.551-564, June 1999.
〔24〕D. Chai and A. Bouzerdoum, “A Bayesian Approach to Skin Color Classification in YCbCr Color Space,” TENCON 2000. Proceedings, IEEE, Kuala Lumpur Malaysia, Vol. 2, pp. 421-424, Sept. 2000.
〔25〕R. C. Gonzalez and R. E. Woods 著，數位元影像處理，繆紹綱譯，台灣培生教育出版，台北，民國九十三年。
〔26〕C. Garcia, and G.Tziritas. “ Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis.” in IEEE Transactions on Multimedia Vol. 1 , No. 3 , pp. 264-277, 1999.
〔27〕L. G. Shapiro, G. C. Stockman, “Computer Vision,” pp.65-68, Prentice-Hall, NJ, 2001.