Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Compensation for Fast Head Movements on Non-intrusive Eye Gaze Tracking System Using Kalman Filter

Kalman filter를 이용한 비접촉식 응시점 추정 시스템에서의 빠른 머리 이동의 보정

  • Kim, Soo-Chan (Hankyong National University Graduate School of Bio and Information Technology) ;
  • Yoo, Jae-Ha (Hankyong Natinal University of Electronis Engineering) ;
  • Kim, Deok-Won (Yonsei University College of Medicine)
  • 김수찬 (한경대학교 생물환경.정보통신 전문대학원) ;
  • 유재하 (한경대학교 전자공학과) ;
  • 김덕원 (연세대학교 의과대학)
  • Published : 2007.11.25
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Abstract

We proposed an eye gaze tracking system under natural head movements. The system consists of one CCD(charge-coupled device) camera and two front-surface mirrors. The mirrors rotate to follow head movements in order to keep the eye within the view of the camera. However, the mirror controller cannot guarantee the fast head movements, because the frame rate is generally 30Hz. To overcome this problem, we applied Kalman filter to estimate next eye position from the current eye image. In the results, our system allowed the subjects head to move 60cm horizontally and 40cm vertically, with the head movement speed about 55cm/sec and 45cm/sec, respectively. And spatial gate resolutions were about 4.5 degree and 5.0 degree, respectively, and the gaze estimation accuracy was 92% under natural head movements.

자연스러운 머리 움직임 하에서 응시점을 추정할 수 있는 시스템을 제안하였다. 이 시스템은 하나의 카메라와 2개의 거울로 구성되어 있으며, 이 거울은 안구에서 눈동자의 영상을 언제나 카메라로 획득할 수 있도록 유지시키는 기능을 한다. 그러나 영상의 획득 속도가 초당 30 프레임이므로 거울의 제어가 빠른 머리 움직임을 보상할 수 없다. 이러한 문제점을 극복하고자 현재 안구 이미지에서 다음 안구 이미지의 위치를 추정하기 위하여 Kalman filter를 적용하였다. 그 결과 수평방향으로 평균 55cm/s, 수직 방향으로 평균 45cm/s정도의 속도의 머리 움직임에 대한 보상이 가능하였다. 그리고, 머리 움직임의 공간도 수평 60cm, 수직 30cm의 넓은 범위까지 가능하였다. 공간 해상도는 수평과 수직 각각 $4.5^{\circ}$와 $5^{\circ}$ 였고, 자연스러운 머리 움직임 아래에서의 응시점의 정확도는 92% 였다.

Keywords

References

  1. Tutis Vilis, http://www.physpharm.fmd.uwo.ca
  2. H. Bekkering and S.F.W. Neggers, 'Visual search is modulated by action intentions,' Psychological Science, 13, pp. 370-374, 2002 https://doi.org/10.1111/j.0956-7976.2002.00466.x
  3. M. L. Phillips and A.S. David, 'Visual scan paths are abnormal in deluded schizophrenics,' Neuropsychologia, vol. 35, pp. 99-105, 1997 https://doi.org/10.1016/S0028-3932(96)00061-9
  4. M. J. Green, L. M. Williams, D. Davidson, 'Visual scanpaths to threat-related faces in deluded schizophrenia,' Psychiatry Res. vol. 119(3), pp.271-85, 2003 https://doi.org/10.1016/S0165-1781(03)00129-X
  5. G. Csibra, 'Teleological and referential understanding of action in infancy,' Philos Trans R Soc Lond B Biol Sci, vol. 358, pp. 447-58, 2003 https://doi.org/10.1098/rstb.2002.1235
  6. M. K. Tanenhaus and M. J. SpiveyKnowlton, 'Eye-tracking,' Language and Cognitive Processes, vol. 11, pp. 583-588, 1996 https://doi.org/10.1080/016909696386971
  7. Q. Ji and X. J. Yang 'Real-time eye, gaze, and face pose tracking for monitoring driver vigilance,' Real-Time Imaging, 8, pp. 357-377, 2002 https://doi.org/10.1006/rtim.2002.0279
  8. 이의철 박강령 조용주, '1인칭 슈팅 게임에서 눈동자 시선 추적에 의한 3차원 화면 조정,' 멀티미디어학회논문지, 제8권, 제10호, 1293-1305쪽, 2005
  9. Y. Ebisawa, 'Improved video-based eye-gaze detection method,' Instrumentation and Measurement, IEEE Transactions on, vol. 47, pp. 948-955, 1998 https://doi.org/10.1109/19.744648
  10. R. B. Murray, M. H. Loughnane, 'Infrared video pupillometry: a method used to measure the pupillary effects of drugs in small laboratory animals in real time,' J Neurosci Methods 1981; 3: 365-75 https://doi.org/10.1016/0165-0270(81)90024-8
  11. D. Robinson, 'A method of measuring eye movement using a scleral search coil in a magnetic field,' IEEE Trans Biomed Eng, vol 10, pp.137-45, 1963
  12. D. Zhu, S.T. Moore, T. Raphan, 'Robust pupil center detection using a curvature algorithm,' Comput Methods Programs Biomed vol. 59: 145-57, 1999 https://doi.org/10.1016/S0169-2607(98)00105-9
  13. 김수찬, M. Sked, Q.. Ji, '머리 움직임이 자유로운 안구 응시 추정 시스템,' 전자공학회논문지, 제41권 SC편, 제5호, 57-64쪽, 2004년 9월
  14. O. Takehiko, M. Naoki, 'A free-head, simple calibration, gaze tracking system that enables gaze-based interaction,' in Proc. of the 2004 symposium on Eye tracking research & applications, pp. 115-122, San Antonio, USA, March, 2004
  15. H. Craig, N. Borna, L. Peter, 'A single camera eye-gaze tracking system with free head motion,' in Proc. of the 2006 symposium on Eye tracking research & applications, pp.87-94, San Diego, USA, March, 2006
  16. D. H. Yoo, M. J. Chung, 'A novel non-intrusive eye gaze estimation using cross-ratio under large head motion,' Computer Vision and Image Understanding, Vol98, Issue 1, 25-51, 2005 https://doi.org/10.1016/j.cviu.2004.07.011
  17. B. Noureddin, P. D. Lawrence, C. F. Man, 'A non-contact device for tracking gaze in a human computer interface,' Computer Vision and Image Understanding, vol. 98, Issue 1, 52-82, 2005 https://doi.org/10.1016/j.cviu.2004.07.005
  18. Y. Ebisawa, M. Ohtani, A. Sugioka, S. Esaki, 'Single mirror tracking system for free-head video-based eye-gazedetection method,' Engineering in Medicine and Biology society, 1997. Proceedings of the 19th Annual International Conference of the IEEE, vol. 4, pp. 1448-1451, 1997
  19. Greg Welch and Gary Bishop, An Introduction to the Kalman Filter, http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html, July, 2006
  20. D. F. Specht, 'A General Regression Neural Network,' IEEE Transactions on Neural Networks, vol.2, pp. 568-576, 1991 https://doi.org/10.1109/72.97934