眼動追蹤一直被應用於認知心理學相關的研究，近年來眼動追蹤更成為人機互動相當熱門的發展重點之一。事實上，眼動追蹤不但能夠被用於輔助行動不便的病患透過電腦與人溝通，也能應用於偵測駕駛精神狀態上，減少駕駛因過度疲勞造成的車禍率，除了可挽救許多人命外，更可降低社會成本。
然而，市面上的眼動追蹤系統經常價格不斐且不易取得，因此我們提出一個只要個人電腦及一個網路攝影機就能使用的眼動追蹤方法。我們修改了Adaboost的人臉追蹤方式，以期調高偵測速度並降低偵測錯誤率，也提出一個能夠快速尋找到虹膜中心位置的方法。最後透過支持向量機，判斷視線可能坐落的區塊，再透過我們設計的視線追蹤機制，進行最終視線所在區塊的判斷。

Eye-tracking systems are wildly used in cognitive psychology research problems, and recently eye-tracking technology has been considered as a potential multimedia interaction way. It can be applied to help people who suffer from disease and lost the ability of controlling their movements, so that they can manipulate computers and communicate with others. In addition, eye-tracking system can also be used to detect drivers’ fatigue. Reducing the number of accidents can not only save lives but also decrease society cost.
However, commercially available eye-tracking systems usually endure with high cost and hard to fetch problems. We propose an eye movement tracking method using personal computer and single webcam. Our method modifies the Adaboost face detection algorithm to make it faster and reduce the false positive rate. We also provide a new method to calculate the center of iris quickly. Finally, we use SVM to help us categories possible gaze region and determine the final gaze region with our gaze tracking mechanism.

[1] A. P. a. L. J.Ball, "Eye tracking in Human-Computer Interaction and Usability Research: Current Status and Future Prospects," in Encyclopedia of Human-Computer Interaction, ed, 2005.
[2] K. S. K. R Jacob, "Eye Tracking in Human-Computer Interaction and Usability Research," 2003.
[3] E. M, "Eye-tracking for detection of driver fatigue," presented at the IEEE Intelligent Transportation System, 1997.
[4] S. Saito, "Does fatigue exist in a quantitative measurement of eye movements?," Ergonomics, vol. 35, 1992.
[5] F. Corno, L. Farinetti, and I. Signorile, "A cost-effective solution for eye-gaze assistive technology " presented at the IEEE International Conference on Multimedia and Expo (ICME), 2002.
[6] X. a. F.-X. H. Dreze, "Internet Advertising: Is Anybody Watching?," Interactive Marketing, vol. 17, pp. 8-23, 2003.
[7] M. C. B. T.K.Leung, P.Perona, "Finding Face in Cluttered Scenes Using Random Labeled Graph Matching," presented at the 15th IEEE Computer Vision, 1995.
[8] C. Garcia and G. Tziritas, "Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis," Ieee Transactions on Multimedia, vol. 1, 1999.
[9] L. Jordao, M. Perrone, J. P. Costeira, and J. Santos-Victor, "Active Face and Feature Tracking," presented at the 10th International Conference on Image Analysis and Processing (ICIAP'99), Venice, Italy, 1999.
[10] R.-L. Hsu, M. Abdel-Mottaleb, and A. K. Jain, "Face Detection in Color Image," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, pp. 696-706, 2002.
[11] F. Marqués and V. Vilaplana, "A morphological approach for segmentation and tracking of human faces," presented at the 15th International Conference on Pattern Recognition (ICPR'00), Barcelona, Spain, 2000.
[12] D. T. I. Craw, and A. Bennett, "Finding Face Features," in second European Conference of Computer Vision, 1996, pp. 142-147.
[13] M. T. a. A.Pentland, "Eigenface for Recognition," Cognitive Neuroscience, vol. 3, pp. 71-86, 1991.
[14] S. B. H. Rowley, and T. Kanade, "Neural Network-Based Face Detection," IEEE Pattern Analysis and Matchine Intelligence, vol. 20, 1998.
[15] K. K. A. Rajagopalan, J.Karlekar,R. Manivasakan,M. Patil,U. Desai, P. Poonacha, and S. Chaudhuri, "Finding Faces in Photographs," in 16th IEEE Computer Vision, 1998.
[16] J. Ren and X. Jiang, "Fast eye localization based on pixel differences " presented at the 16th IEEE International Conference on Image Processing(ICIP), Cairo, 2009.
[17] P. M. D. Sidibe, and S. Janaqi, "A simple and efficient eye detection method in color images," in Image and Vision Computing, New Zealand, Great Barrier Island, 2006.
[18] S. C. K. J.B. Kim, and J.Y. Kim, "Fast detection of multi-view face and eye based on cascaded classifier," in IAPR Conference on Machine Vision Applications, 2005.
[19] W. Z. H. Lu, and D. Yang, "Eye detection based on rectangle features and pixel-pattern-based texture features," presented at the International Symposium on Intelligent Signal Processing and Communication System, 2007.
[20] N. T. Shinjiro Kawato, "Detection and tracking of eyes for gaze-camera control," in 15th International Conference on Vision Interface, 2004, pp. 1031-1038.
[21] D. L. W. Shrinivas J. Pundlik, Stanley T. Birchfild, "Non-Ideal Iris Segmentation Using Graph Cuts," presented at the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008.
[22] B. L. Nguyen, Y. Chahir, M. Molina, C. Tijus, and F. Jouen, "Eye gaze tracking with free head movements using a single camera," presented at the SoICT '10 Proceedings of the 2010 Symposium on Information and Communication Technology Hanoi, Vietnam, 2010.
[23] W. Sewell and O. Komogortsev, "Real-Time Eye Gaze Tracking With an Unmodified Commodity Webcam Employing a Neural Network," presented at the 28th of the international conference extended abstracts on Human factors in computing systems, Atlanta, Georgia, USA, 2010.
[24] P. Viola and M. J. Jones, "Robust Real-Time Face Detection," International Jounrnal of Computer Vision, vol. 57, pp. 137-154, 2004.
[25] N. Otsu, "A Threshold Selection Method from Gray-Level Histograms," IEEE Transactions on Systems, Man and Cybernetics, vol. 9, pp. 62-66, 1979.
[26] K. Peng, L. Chen, S. Ruan, and G. Kukharev, "A Robust Algorithm for Eye Detection on Gray Intensity Face without Spectacles," Journal of Computer Science & Technology, vol. 5, pp. 127-132, 2005.
[27] P. S. H. C.-P. C. a. T.-M. T. Jen-Chun Lee, "Novel and Fast Approach for Iris Location," presented at the Intelligent Information Hiding and Multimedia Signal Processing, 2007, 2008.
[28] J. Thorsten, "Making Large-scale SVM learning practical," in Advances in Kernel Methods, ed: MIT Press, 1999, pp. 169-184.
[29] C. J. C. Burges, "A tutorial on Support Vector Machines for Pattern Recognition," Data Mining and Knowledge Discovery, vol. 2, pp. 121-167, 1998.
[30] C.-C. C. a. C.-J. Lin, "LIBSVM: a library for support vector machines.," ed: ACM Transcations on Intelligent Systems and Technology, 2011.
[31] U. o. Stirling, "The Psychological Image Collection at Stirling," U. o. Stirling, Ed., ed. pics.stir.ac.uk.
[32] C. I. o. Technology, "Faces 1999," C. I. o. Technology, Ed., ed, 1999.
[33] P. J. Phillips, K. W. Bowyer, and P. J. Flynn, "CASIA Iris Image Database(ver 1.0)," ed, 2007.
[34] J. Daugman, "High Confidence Visual Recognition of Persons by a Test of Statistical Independnce," IEEE Transactions on PAMI, vol. 15, 1993.
[35] J. Daugman, "How iris Recognition Works," Proceedings of 2002 International Conference on Image Processing, vol. 1, 2002.
[36] J. Daugman, "The Improtance of Being Random: Statical Principles of Iris Recognition," Pattern Recognition, vol. 36, pp. 279-291, 2003.