A Data-Driven Approach for Gaze Tracking

Gaze tracking presents an intuitive interface for technology in today’s society, with its application focus in controlling electronic devices. This paper concentrates on the design and application of an automatic gaze tracking system utilizing commodity equipment. Compared to preceding low-cost methods, the proposed method is significantly simpler, lowering the barrier of entry for this type of device, and can potentially afford more accurate tracking. Through the careful placement of the infrared (IR) light-emitting-diodes (LEDs) on the monitor and coaxially to the optical axis of the camera, the pupil was illuminated and reference glints became visible on the cornea. These glints were captured by a camera capable of detecting IR light, and were used to determine the users line of sight relative to the monitor. A linear model was used to address the horizontal and vertical components of the glints in the users eye and match them to the corresponding location point on the monitor. K-means clustering was utilized to classify the separate gaze regions with promising results.

[1]  Sungsoo Lim,et al.  Real-Time Eye Tracking Using IR Stereo Camera for Indoor and Outdoor Environments , 2017, KSII Trans. Internet Inf. Syst..

[2]  Junjie Wu,et al.  Advances in K-means Clustering , 2012, Springer Theses.

[3]  Yan Zhang,et al.  Big data-informed energy efficiency assessment of China industry sectors based on K-means clustering , 2018 .

[4]  Yanpeng Cai,et al.  Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China. , 2016, The Science of the total environment.

[5]  Kenneth P. Camilleri,et al.  Unobtrusive and pervasive video-based eye-gaze tracking , 2018, Image Vis. Comput..

[6]  Ba Linh Nguyen Eye Gaze Tracking , 2009, 2009 IEEE-RIVF International Conference on Computing and Communication Technologies.

[7]  Andrew P. Bradley,et al.  The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..

[8]  Kang Ryoung Park,et al.  New computer interface combining gaze tracking and brainwave measurements , 2011, IEEE Transactions on Consumer Electronics.

[9]  Moshe Eizenman,et al.  Analysis of subject-dependent point-of-gaze estimation bias in the cross-ratios method , 2008, ETRA.

[10]  Kang Ryoung Park,et al.  Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor , 2018, Sensors.

[11]  David J. Fleet,et al.  Cartesian K-Means , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Cheng Zhang,et al.  An Eye-Gaze Tracking and Human Computer Interface System for People with ALS and other Locked-in Diseases , 2012 .

[13]  Bin Li,et al.  Etracker: A Mobile Gaze-Tracking System with Near-Eye Display Based on a Combined Gaze-Tracking Algorithm , 2018, Sensors.

[14]  Moshe Eizenman,et al.  Investigation of the Cross-Ratios Method for Point-of-Gaze Estimation , 2008, IEEE Transactions on Biomedical Engineering.

[15]  Myung Jin Chung,et al.  A novel non-intrusive eye gaze estimation using cross-ratio under large head motion , 2005, Comput. Vis. Image Underst..

[16]  H. Ahn,et al.  Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis , 2011, Schizophrenia Research.

[17]  Kang Ryoung Park,et al.  Gaze Tracking System for User Wearing Glasses , 2014, Sensors.

[18]  M Adjouadi,et al.  A practical EMG-based human-computer interface for users with motor disabilities. , 2000, Journal of rehabilitation research and development.

[19]  C. Sears,et al.  Eye gaze tracking reveals heightened attention to food in adults with binge eating when viewing images of real-world scenes , 2015, Appetite.

[20]  Kang Ryoung Park,et al.  Compensation Method of Natural Head Movement for Gaze Tracking System Using an Ultrasonic Sensor for Distance Measurement , 2016, Sensors.

[21]  Taikang Ning,et al.  A human-computer interface design using automatic gaze tracking , 2012, 2012 IEEE 11th International Conference on Signal Processing.

[22]  Nesrin Aydin Atasoy,et al.  Real-time motorized electrical hospital bed control with eye-gaze tracking , 2016 .

[23]  Jianzhong Wu,et al.  k-means based load estimation of domestic smart meter measurements , 2017 .

[24]  Myung Jin Chung,et al.  Non-contact eye gaze tracking system by mapping of corneal reflections , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[25]  Fengliang Xu,et al.  Real-time eye detection and tracking for driver observation under various light conditions , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[26]  D.M. Mount,et al.  An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Hong Hua,et al.  Video-based eyetracking methods and algorithms in head-mounted displays. , 2006, Optics express.

[28]  Li Xia,et al.  Accurate gaze tracking from single camera using gabor corner detector , 2014, Multimedia Tools and Applications.