Iris Feature-Based 3-D Gaze Estimation Method Using a One-Camera-One-Light-Source System

被引:15
作者
Liu, Jiahui [1 ]
Chi, Jiannan [1 ]
Lu, Ning [1 ]
Yang, Zuoyun [1 ]
Wang, Zhiliang [2 ]
机构
[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
[2] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
关键词
Three-dimensional displays; Estimation; Gaze tracking; Calibration; Head; Cameras; Iris; 3-D gaze estimation; iris radius; kappa angle; one-camera-one-light-source (OCOLS); user calibration; TRACKING TECHNIQUES; SINGLE CAMERA; EYE;
D O I
10.1109/TIM.2019.2956612
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Multicamera or multilight-source is generally used to estimate the 3-D coordinates of the cornea center for 3-D gaze estimation in the existing gaze trackers. Although some model-based methods use one-camera systems to estimate 3-D gazes, which include some user-dependent eye parameters preset by fixed values, a one-camera-one-light-source system is still unable to achieve 3-D gaze estimation by considering individual differences. In this article, an iris feature-based method using one camera and one light source for 3-D gaze estimation is proposed. The iris radius and the kappa angle are determined during user calibration. The optical axis is reconstructed by the iris center and its normal vector from only the iris features. Therefore, with the real-time estimation of kappa angle, the 3-D gaze is estimated by an optimization method. Computer simulations and practical experiments have been performed to analyze the feasibility and robustness of the proposed method. This article's innovation lies in achieving 3-D gaze estimation based on only one-camera and one-light source with calibrated eye-specific parameters, which breaks through the limitation of the existing methods using a 3-D cornea center on the system's hardware requirements of 3-D gaze estimation. The simplified hardware system has great application values, especially in the portable mobile devices widely used today. Moreover, a binocular model is used to optimize the results of the point of regard, which improves the accuracy of 3-D gaze estimation effectively.
引用
收藏
页码:4940 / 4954
页数:15
相关论文
共 43 条
[1]  
[Anonymous], 1999, Nat Med, V5, P1229
[2]  
Beymer D, 2003, PROC CVPR IEEE, P451
[3]  
Blignaut P, 2014, J EYE MOVEMENT RES, V7
[4]   Gazing point dependent eye gaze estimation [J].
Cheng, Hong ;
Liu, Yaqi ;
Fu, Wenhao ;
Ji, Yanli ;
Yang, Lu ;
Zhao, Yang ;
Yang, Jie .
PATTERN RECOGNITION, 2017, 71 :36-44
[5]   Eye Gaze Tracking With a Web Camera in a Desktop Environment [J].
Cheung, Yiu-ming ;
Peng, Qinmu .
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2015, 45 (04) :419-430
[6]  
Coutinho FL, 2006, SIBGRAPI, P171
[7]   Improved video-based eye-gaze detection method [J].
Ebisawa, Y .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 1998, 47 (04) :948-955
[8]   Remote point-of-gaze estimation with free head movements requiring a single-point calibration [J].
Guestrin, Elias Daniel ;
Eizemnan, Moshe .
2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16, 2007, :4556-+
[9]   General theory of remote gaze estimation using the pupil center and corneal reflections [J].
Guestrin, Elias Daniel ;
Eizenman, Moshe .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2006, 53 (06) :1124-1133
[10]  
Hansen D.W., 2010, P 2010 S EYE TRACKIN, P13, DOI DOI 10.1145/1743666.1743670