| Peer-Reviewed

A New Method for Calibration of Kappa Angle in 3D Line of Sight Tracking System

Received: 19 July 2018     Published: 20 July 2018
Views:       Downloads:
Abstract

At present, the general idea of the 3D line of sight (LoS) estimation is as follows. First, the direction of the 3D line of gaze (LoG) can be reconstructed according to the visual characteristics of the eyeballs (pupil center coordinates, purkinje images coordinates, etc.). Then the transformation matrix of the direction of LoG and the direction of LoS can be calculated based on the Kappa angle between LoG and LoS. LoS can be estimated with known LoG. The transformation matrix between LoG and LoS is usually determined by the user calibration process of the gaze tracking system. Because the eyeball structure is unique and the Kappa is a space angle, the transformation matrix changes with the space location of the eyeball. This paper elaborates on the Kappa angle calibration problem in the gaze tracking system. A new calibration and calculation method of Kappa angle is proposed in this paper, which can solve the calculation of space Kappa angle in the case of head translation, pitch and rotation. Simulation and experimental results verify the effectiveness of the proposed method.

Published in Science Innovation (Volume 6, Issue 4)
DOI 10.11648/j.si.20180604.12
Page(s) 182-189
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Gaze Tracking, Kappa Angle, Line of Sight, Line of Gaze

References
[1] Chamberlain L. Eye Tracking Methodology; Theory and Practice [J]. Qualitative Market Research, 2013 (2).
[2] Choi K A, Ma C, Ko S J. Improving the usability of remote eye gaze tracking forhuman-device interaction [J]. Consumer Electronics, IEEE Transactions on, 2014, 60(3): 493-498.
[3] Zhu J, Yang J. Subpixel Eye Gaze Tracking[C].IEEE International Conference on Automatic Face and Gesture Recognition, 2002. Proceedings. 2002:124-129.
[4] Morimoto C H, Mimica M R M. Eye gaze tracking techniques for interactive applications [J]. Computer Vision & Image Understanding, 2005, 98(1):4-24.
[5] Jose Sigut and Sid-Ahmed Sidha. Iris Center Corneal Reflection Method for Gaze TrackingUsing Visible Light[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2011,58(2):411-421.
[6] Shao G, Che M, Zhang B, et al. A Novel Simple 2D Model of Eye Gaze Estimation[C]. International Conference on Intelligent Human-Machine Systems & Cybernetics. IEEE Computer Society, 2010:300-304.
[7] Valenti R, Sebe N, Gevers T. Combining Head Pose and Eye Location Information for Gaze Estimation [J]. IEEE Transactions on Image Processing, 2012, 21(2):802-815.
[8] Shih S W, Liu J. A novel approach to 3-D gaze tracking using stereo cameras.[J]. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society, 2004, 34(1):234-45.
[9] Hennessey C, Noureddin B, Lawrence P. A single camera eye-gaze tracking system with free head motion [J]. Proceedings of Etra Eye Tracking Research & Applications Symposium, 2006:87-94.
[10] Elias Daniel G, Moshe E. General theory of remote gaze estimation using the pupil center and corneal reflections [J]. IEEE Transactions on Biomedical Engineering, 2006, 53(6):1124-1133.
[11] Dong H Y, Chung M J. Eye-mouse under large head movement for human-computer interface[C]. IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA. IEEE, 2004:237-242 Vol.1.
[12] ED Guestrin, M Eizenman. Remote point-of-gaze estimation with free head movements requiring a single-point calibration. International Conference of the IEEE Engineering in Medicine & Biology Society, 2007, 2007:4556-60.
[13] Sheng-Wen Shih, Jin Liu. A Novel Approach to 3D Gaze Tracking Using Stereo Cameras[J]. IEEE TRANSZETIONS ON SYSTEMS MAN AND CYBERNETICS-PART B: CYBERNETICS.2004, 34(1):234-256.
[14] Arantxa Villanueva and Rafael Cabeza. A Novel Gaze Estimation System With One Calibration Point[J]. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 38, NO. 4, AUGUST 2008.
[15] Zhu Z, Ji Q. Robust real-time eye detection and tracking under variable lighting conditions and various face orientations[J].Computer Vision and Image Understanding, 2005, 98(1): 124-154.
[16] Chih-Chuan Lai, Sheng-Wen Shih, Member, IEEE, and Yi-Ping Hung. Hybrid Method for 3-D Gaze Tracking Using Glint and Contour Features[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 25, NO. 1, JANUARY 2015.
Cite This Article
  • APA Style

    Lu Ning, Zhang Guosheng, Chi Jiannan. (2018). A New Method for Calibration of Kappa Angle in 3D Line of Sight Tracking System. Science Innovation, 6(4), 182-189. https://doi.org/10.11648/j.si.20180604.12

    Copy | Download

    ACS Style

    Lu Ning; Zhang Guosheng; Chi Jiannan. A New Method for Calibration of Kappa Angle in 3D Line of Sight Tracking System. Sci. Innov. 2018, 6(4), 182-189. doi: 10.11648/j.si.20180604.12

    Copy | Download

    AMA Style

    Lu Ning, Zhang Guosheng, Chi Jiannan. A New Method for Calibration of Kappa Angle in 3D Line of Sight Tracking System. Sci Innov. 2018;6(4):182-189. doi: 10.11648/j.si.20180604.12

    Copy | Download

  • @article{10.11648/j.si.20180604.12,
      author = {Lu Ning and Zhang Guosheng and Chi Jiannan},
      title = {A New Method for Calibration of Kappa Angle in 3D Line of Sight Tracking System},
      journal = {Science Innovation},
      volume = {6},
      number = {4},
      pages = {182-189},
      doi = {10.11648/j.si.20180604.12},
      url = {https://doi.org/10.11648/j.si.20180604.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20180604.12},
      abstract = {At present, the general idea of the 3D line of sight (LoS) estimation is as follows. First, the direction of the 3D line of gaze (LoG) can be reconstructed according to the visual characteristics of the eyeballs (pupil center coordinates, purkinje images coordinates, etc.). Then the transformation matrix of the direction of LoG and the direction of LoS can be calculated based on the Kappa angle between LoG and LoS. LoS can be estimated with known LoG. The transformation matrix between LoG and LoS is usually determined by the user calibration process of the gaze tracking system. Because the eyeball structure is unique and the Kappa is a space angle, the transformation matrix changes with the space location of the eyeball. This paper elaborates on the Kappa angle calibration problem in the gaze tracking system. A new calibration and calculation method of Kappa angle is proposed in this paper, which can solve the calculation of space Kappa angle in the case of head translation, pitch and rotation. Simulation and experimental results verify the effectiveness of the proposed method.},
     year = {2018}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - A New Method for Calibration of Kappa Angle in 3D Line of Sight Tracking System
    AU  - Lu Ning
    AU  - Zhang Guosheng
    AU  - Chi Jiannan
    Y1  - 2018/07/20
    PY  - 2018
    N1  - https://doi.org/10.11648/j.si.20180604.12
    DO  - 10.11648/j.si.20180604.12
    T2  - Science Innovation
    JF  - Science Innovation
    JO  - Science Innovation
    SP  - 182
    EP  - 189
    PB  - Science Publishing Group
    SN  - 2328-787X
    UR  - https://doi.org/10.11648/j.si.20180604.12
    AB  - At present, the general idea of the 3D line of sight (LoS) estimation is as follows. First, the direction of the 3D line of gaze (LoG) can be reconstructed according to the visual characteristics of the eyeballs (pupil center coordinates, purkinje images coordinates, etc.). Then the transformation matrix of the direction of LoG and the direction of LoS can be calculated based on the Kappa angle between LoG and LoS. LoS can be estimated with known LoG. The transformation matrix between LoG and LoS is usually determined by the user calibration process of the gaze tracking system. Because the eyeball structure is unique and the Kappa is a space angle, the transformation matrix changes with the space location of the eyeball. This paper elaborates on the Kappa angle calibration problem in the gaze tracking system. A new calibration and calculation method of Kappa angle is proposed in this paper, which can solve the calculation of space Kappa angle in the case of head translation, pitch and rotation. Simulation and experimental results verify the effectiveness of the proposed method.
    VL  - 6
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • School of Automation & Electrical Engineering, University of Science and Technology Beijing, Beijing, PRC

  • Ministry of Transport of the People's Republic of China, Key Laboratory of Operation Safety Technology on Transport Vehicle, Beijng, PRC

  • School of Automation & Electrical Engineering, University of Science and Technology Beijing, Beijing, PRC

  • Sections