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Facial Gaze Detection by Estimating Three Dimensional Positional Movements  

Park, Gang-Ryeong (LG 전자기술원)
Kim, Jae-Hui (연세대학교 전기·컴퓨터공학과)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.39, no.3, 2002 , pp. 23-35 More about this Journal
Abstract
Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a single camera above a monitor and a user moves (rotates and/or translates) his face to gaze at a different position on the monitor. To detect the gaze position, we locate facial region and facial features(both eyes, nostrils and lip corners) automatically in 2D camera images. From the movement of feature points detected in starting images, we can compute the initial 3D positions of those features by camera calibration and parameter estimation algorithm. Then, when a user moves(rotates and/or translates) his face in order to gaze at one position on a monitor, the moved 3D positions of those features can be computed from 3D rotation and translation estimation and affine transform. Finally, the gaze position on a monitor is computed from the normal vector of the plane determined by those moved 3D positions of features. As experimental results, we can obtain the gaze position on a monitor(19inches) and the gaze position accuracy between the computed positions and the real ones is about 2.01 inches of RMS error.
Keywords
Gaze Detection; camera calibration; parameter estimation; 3D motion estimation;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Steven C. Chapra, Raymond P. Canale, 'Numerical Methods for Engineers', McGraw-Hill International Editions, 1989
2 R. BROWN et al., Introduction To Random Signals and Applied Kalman Filtering, Wiley, Third Edition
3 J. Heinzmann, A. Zelinsky, '3-D Facial Pose and Gaze Point Estimation using a Robust Real-Time Tracking Paradigm', Proceedings of the International Conference on Automatic Face and Gesture Recognition, pp. 142-147, 1998   DOI
4 Jaihie Kim, K. R. Park, S. Leclair, 'Process Control via Gaze Detection Technology', The Second International Conference on Intelligent Processing and Manufacturing of Materials, pp.1263-1269, July, 1999   DOI
5 A. Gee, R. Cipolla, 'Fast visual tracking by temporal consensus', Image and Vision Computing', Image and Vision Computing, Vol. 14, pp. 105-114, 1996   DOI   ScienceOn
6 A. Azarbayejani, 'Visually Controlled Graphics', IEEE Trans. PAMI, Vol. 15, No. 6, pp. 602-605, June, 1993   DOI   ScienceOn
7 T. Fukuhara, T. Murakami, '3D-motion estimation of human head for model-based image coding', IEE Proc., Vol. 140, No. 1, pp. 26-35, 1993
8 P. Ballard, G. Stockman, 'Controlling a Computer via Facial Aspect', IEEE Trans. on System Man and Cybernetics, Vol. 25, No.4, pp. 669-677, 1995   DOI   ScienceOn
9 A. Tomono, F. Kishino, 'Gaze Point Detection Algorithm Based on Measuring 3D Positions of Face and Pupil', IEICE Transactions on Information and Systems, D-Ⅱ, Vol. J75-D-Ⅱ, No. 5, pp. 861-872. 1992. 5
10 T. Rikert, M. Jones, 'Gaze Estimation using Morphable Models', Proceedings of the International Conference on Automatic Face and Gesture Recognition, pp. 436-441, 1998   DOI
11 Ramesh Jain, Machine Vision, McGraw-Hill International Edition, 1995
12 박강령, 김재희, '단안 카메라 환경에서의 시선위치 추적', 한국통신학회 논문지, 제26권 10호, pp.1390-1398, 2001년 10월   과학기술학회마을