A Real-Time Video-based Eye Tracking Approach for Driver Attention Study

nowing the driver's point of gaze has significant potential to enhance driving safety, eye movements can be used as an indicator of the attention state of a driver; but the primary obstacle of integrating eye gaze into today's large scale real world driving attention study is the availability of a reliable, low-cost eye-tracking system. In this paper, we make an attempt to investigate such a real-time system to collect driver's eye gaze in real world driving environment. A novel eye-tracking approach is proposed based on low cost head mounted eye tracker. Our approach detects corneal reflection and pupil edge points firstly, and then fits the points with ellipse. The proposed approach is available in different illumination and driving environment from simple inexpensive head mounted eye tracker, which can be widely used in large scale experiments. The experimental results illustrate our approach can reliably estimate eye position with an accuracy of average 0.34 degree of visual angle in door experiment and 2--5 degrees in real driving environments.

[1]  Eli Peli,et al.  Tracking Telescope Aiming Point for Bioptic Driving Surveillance , 2009, IPCV.

[2]  Gang Luo,et al.  Telescope Aiming Point Tracking Method for Bioptic Driving Surveillance , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[3]  Markus Lappe,et al.  Car drivers attend to different gaze targets when negotiating closed vs. open bends. , 2010, Journal of vision.

[4]  Bryan Reimer,et al.  Impact of Cognitive Task Complexity on Drivers’ Visual Tunneling , 2009 .

[5]  H. Vincent Poor,et al.  Outlier elimination for robust ellipse and ellipsoid fitting , 2009, 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[6]  Haruki Kawanaka,et al.  Driver's cognitive distraction detection using physiological features by the adaboost , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[7]  Takashi Imamura,et al.  Detection of view direction with a single camera and its application using eye gaze , 2009, 2009 35th Annual Conference of IEEE Industrial Electronics.

[8]  Sha Sha,et al.  A fast matching algorithm based on K-degree template , 2009, 2009 4th International Conference on Computer Science & Education.

[9]  Riad I. Hammoud,et al.  Passive Eye Monitoring: Algorithms, Applications and Experiments , 2008 .

[10]  Xiaoqing Ding,et al.  Eye/eyes tracking based on a unified deformable template and particle filtering , 2010, Pattern Recognit. Lett..

[11]  Mohan M. Trivedi,et al.  On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes , 2009, IEEE Transactions on Intelligent Transportation Systems.

[12]  Qiang Ji,et al.  In the Eye of the Beholder: A Survey of Models for Eyes and Gaze , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Sei-Wang Chen,et al.  Real-Time Vision-Based Driver Drowsiness/Fatigue Detection System , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[14]  Mohan Trivedi,et al.  Investigating the relationships between gaze patterns, dynamic vehicle surround analysis, and driver intentions , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[15]  Hirotake Yamazoe,et al.  Remote and head-motion-free gaze tracking for real environments with automated head-eye model calibrations , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[16]  Rafael Cabeza,et al.  Evaluation of Corneal Refraction in a Model of a Gaze Tracking System , 2008, IEEE Transactions on Biomedical Engineering.

[17]  Dongheng Li,et al.  Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[18]  Juan C. Burguillo,et al.  History-based Self-Organizing Traffic Lights , 2012, Comput. Informatics.

[19]  Baozong Yuan,et al.  Automatic Eye Feature Extraction in Human Face Images , 2001, Comput. Artif. Intell..

[20]  Shengsheng Yu,et al.  A Survey of Face Detection, Extraction and Recognition , 2003, Comput. Artif. Intell..

[21]  Mahmood Fathy,et al.  Video Shot Boundary Detection Using Generalized Eigenvalue Decomposition and Gaussian Transition Detection , 2009, Comput. Informatics.

[22]  Zhiwei Zhu,et al.  Novel Eye Gaze Tracking Techniques Under Natural Head Movement , 2007, IEEE Transactions on Biomedical Engineering.