journal article·2018-09-30Open access

A Method of Free-Space Point-of-Regard Estimation Based on 3D Eye Model and Stereo Vision

Zijing Wan, Xiangjun Wang, Lei Yin, Kai Zhou

Applied Sciences· Volume 8· Issue 10

Abstract

This paper proposes a 3D point-of-regard estimation method based on 3D eye model and a corresponding head-mounted gaze tracking device. Firstly, a head-mounted gaze tracking system is given. The gaze tracking device uses two pairs of stereo cameras to capture the left and right eye images, respectively, and then sets a pair of scene cameras to capture the scene images. Secondly, a 3D eye model and the calibration process are established. Common eye features are used to estimate the eye model parameters. Thirdly, a 3D point-of-regard estimation algorithm is proposed. Three main parts of this method are summarized as follows: (1) the spatial coordinates of the eye features are directly calculated by using stereo cameras; (2) the pupil center normal is used to the initial value for the estimation of optical axis; (3) a pair of scene cameras are used to solve the actual position of the objects being watched in the calibration process, and the calibration for the proposed eye model does not need the assistance of the light source. Experimental results show that the proposed method can output the coordinates of 3D point-of-regard more accurately.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Gaze Tracking and Assistive Technology · Glaucoma and retinal disorders · Ocular Surface and Contact Lens

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China

MOEMS Education Ministry Key Laboratory, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China

Funding

National Natural Science Foundation of China

References (35)

Show source-provided references
1. In the Eye of the Beholder: A Survey of Models for Eyes and Gaze10.1109/TPAMI.2009.30 ↗
2. Estimating 3-D Point-of-Regard in a Real Environment Using a Head-Mounted Eye-Tracking System10.1109/THMS.2014.2318324 ↗
3. Eye and gaze tracking for visually controlled interactive stereoscopic displays10.1016/S0923-5965(98)00044-7 ↗
4. Gaze position detection by computing the three dimensional facial positions and motions10.1016/S0031-3203(01)00206-0 ↗
5. Guestrin, E.D., and Eizenman, M. (2008, January 26–28). Remote point-of-gaze estimation requiring a single-point calibration for applications with infants. Proceedings of the Symposium on Eye Tracking Research & Applications, Savannah, GA, USA.10.1145/1344471.1344531 ↗
6. Wang, K., and Ji, Q. (2017, January 22–29). Real Time Eye Gaze Tracking with 3D Deformable Eye-Face Model. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.10.1109/ICCV.2017.114 ↗
7. General theory of remote gaze estimation using the pupil center and corneal reflections10.1109/TBME.2005.863952 ↗
8. Novel eye gaze tracking techniques under natural head movement10.1109/TBME.2007.895750 ↗
9. A Novel Gaze Estimation System with One Calibration Point10.1109/TSMCB.2008.926606 ↗
10. Long range eye gaze tracking system for a large screen10.1109/TCE.2012.6414976 ↗
11. A novel non-intrusive eye gaze estimation using cross-ratio under large head motion10.1016/j.cviu.2004.07.011 ↗
12. Beymer, D., and Flickner, M. (2003, January 16–22). Eye gaze tracking using an active stereo head. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Madison, WI, USA.
13. Gaze Detection by Wearable Eye-Tracking and NIR LED-Based Head-Tracking Device Based on SVR10.4218/etrij.12.0111.0193 ↗
14. An Automatic Personal Calibration Procedure for Advanced Gaze Estimation Systems10.1109/TBME.2009.2039351 ↗
15. Chen, J., and Ji, Q. (2011, January 20–25). Probabilistic gaze estimation without active personal calibration. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, CO, USA.10.1109/CVPR.2011.5995675 ↗
16. Calibration method for 3D gaze tracking systems10.1364/AO.56.001536 ↗
17. Zhang, X., Sugano, Y., Fritz, M., and Bulling, A. (2015, January 7–12). Appearance-based gaze estimation in the wild. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.10.1109/CVPR.2015.7299081 ↗
18. 3D Gaze Estimation without Explicit Personal Calibration10.1016/j.patcog.2018.01.031 ↗
19. Eye gaze tracking techniques for interactive applications10.1016/j.cviu.2004.07.010 ↗
20. Gazing point dependent eye gaze estimation10.1016/j.patcog.2017.04.026 ↗
21. Tan, K.H., Kriegman, D.J., and Ahuja, N. (2002, January 3–4). Appearance-based Eye Gaze Estimation. Proceedings of the IEEE Workshop on Applications of Computer Vision, Orlando, FL, USA.
22. Appearance-Based Gaze Estimation via Uncalibrated Gaze Pattern Recovery10.1109/TIP.2017.2657880 ↗
23. Durna, Y., and Ari, F. (2017). Design of a Binocular Pupil and Gaze Point Detection System Utilizing High Definition Images. Appl. Sci., 7.10.3390/app7050498 ↗
24. Real time gaze estimation with a consumer depth camera10.1016/j.ins.2015.02.004 ↗
25. Gaze Estimation from Color Image Based on the Eye Model with Known Head Pose10.1109/THMS.2015.2477507 ↗
26. An investigation on the feasibility of uncalibrated and unconstrained gaze tracking for human assistive applications by using head pose estimation10.3390/s140508363 ↗
27. Real-time gaze estimation with online calibration10.1109/MMUL.2014.54 ↗
28. Gaze Estimation in the 3D Space Using RGB-D Sensors10.1007/s11263-015-0863-4 ↗
29. Li, B., Fu, H., Wen, D., and LO, W. (2018). Etracker: A Mobile Gaze-Tracking System with Near-Eye Display Based on a Combined Gaze-Tracking Algorithm. Sensors, 18.10.3390/s18051626 ↗
30. Huang, C.W., and Tan, W.C. (2016, January 27–29). An approach of head movement compensation when using a head mounted eye tracker. Proceedings of the IEEE International Conference on Consumer Electronics-Taiwan 2016, Nantou, Taiwan.10.1109/ICCE-TW.2016.7520987 ↗
31. Su, D., and Li, Y.F. (2016, January 3–7). Toward flexible calibration of head-mounted gaze trackers with parallax error compensation. Proceedings of the IEEE International Conference on Robotics and Biomimetics 2016, Qingdao, China.10.1109/ROBIO.2016.7866370 ↗
32. Pirri, F., Pizzoli, M., and Rudi, A. (2011, January 20–25). A general method for the point of regard estimation in 3D space. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, CO, USA.10.1109/CVPR.2011.5995634 ↗
33. Wan, Z., Wang, X., Zhou, K., Chen, X., and Wang, X. (2018). A Novel Method for Estimating Free Space 3D Point-of-Regard Using Pupillary Reflex and Line-of-Sight Convergence Points. Sensors, 18.10.3390/s18072292 ↗
34. A novel harris multi-scale corner detection algorithm
35. Haro, A., Flickner, M., and Essa, I. (2000, January 15). Detecting and tracking eyes by using their physiological properties, dynamics, and appearance. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head, SC, USA.