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http://dx.doi.org/10.5302/J.ICROS.2009.15.8.839

A Real-time Eye Tracking Algorithm for Autostereoscopic 3-Dimensional Monitor  

Lim, Young-Shin (호서대학교 디지털디스플레이공학과)
Kim, Joon-Seek (호서대학교 전자공학과)
Joo, Hyo-Nam (호서대학교 디지털디스플레이공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.15, no.8, 2009 , pp. 839-844 More about this Journal
Abstract
In this paper, a real-time eye tracking method using fast face detection is proposed. Most of the current eye tracking systems have operational limitations due to sensors, complicated backgrounds, and uneven lighting condition. It also suffers from slow response time which is not proper for a real-time application. The tracking performance is low under complicated background and uneven lighting condition. The proposed algorithm detects face region from acquired image using elliptic Hough transform followed by eye detection within the detected face region using Haar-like features. In order to reduce the computation time in tracking eyes, the algorithm predicts next frame search region from the information obtained in the current frame. Experiments through simulation show good performance of the proposed method under various environments.
Keywords
eye tracking; face detection; hough transform; haar-like features; edge detection; partial search method;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
Times Cited By SCOPUS : 0
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1 신윤희, 강신국, 김은이, "얼굴 특징 추적을 이용한 인터페이스 구현," 한국정보과학회 학술발표논문집, pp. 274-276,2006
2 L. Hannon & w. Hunt, "Automatic recognition of human face profile,"CVGIP, vol.6,pp.135-156, 1977.
3 이경미, "이질적 템플릿 매칭의 융합을 이용한 얼굴 영역 검출," 한국콘테츠학회논문지, 제7권 제12호, pp311-321,2007   DOI
4 I. Craw, D. Tock, and A. Bennett, "Finding face features," In proc. ECCV, pp. 92-96, 1992   DOI
5 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   DOI   ScienceOn
6 D. Beymer, "Face recognition under varying pose," In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 756-761,1994
7 T. Kawaguchi and M. Rizon, "Iris detection using intensity and edge information," Pattern Recognition, vol. 36, no. 22, pp. 549-562,2003.   DOI   ScienceOn
8 P. Viola and M. Jones, "Robust real-time object detection," International Journal of Computer Vision, pp. 137-154, 2002
9 R. Lienhart and J. Maydt, "An extended set ofhaar-like features for rapid object detection," IEEE ICIP 2002, vol. 1, pp. 900-903, 2002
10 J. Canny, "A computational approach to edge detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, no. 6,pp. 679-698, 1986   DOI   ScienceOn
11 K.-C. Jin and J-H Cho, "Automatic face feature tracking," proceedings of the 1999 IEEE Region 10 Conference TENCON' 99, vol. 1, pp. 68-71, Cheju, Korea, 1999   DOI
12 E. Hjelmas, "Face detection: a survey," Comput-er Vision and Image Understanding, vol. 83, pp. 236-274, 2001   DOI   ScienceOn
13 G Xu and T. Sugimoto, "Rits eye: a software-based syst-em for real-time face detection and tracking using pan-ti-It-zoom controllable camera," in Proc. of International Conference on Pattern Recognition, vol. 2, pp. 1194-1197, 1998