Pupil detection and gaze tracking using a deformable template

This paper suggests a method for tracking gaze of a person at a distance around 2 m, using a single pan-tilt-zoom (PTZ) camera. In the suggested method, images are acquired for gaze tracking by turning the camera to the wide angle mode, or the narrow angle mode, depending on the location of the person. The face that is present in the field of view (FOV) of a camera, is detected in the wide angle mode. Once the location of the face is calculated, the camera turns to the narrow angle mode. The images, which have been acquired in the narrow angle mode, contain information on the direction of gaze of the person, who is at a distance. The method for calculating the direction of gaze is comprised of the head pose estimation and gaze direction calculation steps. The head pose estimation is performed using the location information on the eyes and nose in the face. The direction of gaze is generated using the process of partitioning the pupil through a deformable template, and extracting the center of an eye using the end points of both eyes and head pose information. This paper shows that the proposed gaze tracking algorithm can effectively track the direction of a person’s gaze, at varying distances.

[1]  Yoshimitsu Aoki,et al.  Unconstrained and Calibration-Free Gaze Estimation in a Room-Scale Area Using a Monocular Camera , 2018, IEEE Access.

[2]  Chern-Sheng Lin,et al.  Active Eye-tracking System by Using Quad PTZ Cameras , 2007, IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society.

[3]  Soo-Young Lee,et al.  Smart user interface for mobile consumer devices using model-based eye-gaze estimation , 2013, IEEE Transactions on Consumer Electronics.

[4]  Yoichi Sato,et al.  Appearance-Based Gaze Estimation via Uncalibrated Gaze Pattern Recovery , 2017, IEEE Transactions on Image Processing.

[5]  Kang Ryoung Park,et al.  Gaze tracking system at a distance for controlling IPTV , 2010, IEEE Transactions on Consumer Electronics.

[6]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[7]  Gian Luca Marcialis,et al.  Exploiting the Golden Ratio on Human Faces for Head-Pose Estimation , 2013, ICIAP.

[8]  Ronan G. Reilly,et al.  Current trends in eye tracking research , 2014 .

[9]  Peter M. Corcoran,et al.  Real-time eye gaze tracking for gaming design and consumer electronics systems , 2012, IEEE Transactions on Consumer Electronics.

[10]  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.

[11]  Lu Yang,et al.  Gazing point dependent eye gaze estimation , 2017, Pattern Recognit..

[12]  Lin Kunhui,et al.  Real-time non-intrusive eye tracking for human-computer interaction , 2010, 2010 5th International Conference on Computer Science & Education.

[13]  Samarth Bharadwaj,et al.  Adaptive Skin Color Model to Improve Video Face Detection , 2016 .

[14]  Whoi-Yul Kim,et al.  Long-Range Gaze Tracking System for Large Movements , 2013, IEEE Transactions on Biomedical Engineering.

[15]  B W Baker,et al.  The role of the divine proportion in the esthetic improvement of patients undergoing combined orthodontic/orthognathic surgical treatment. , 2001, The International journal of adult orthodontics and orthognathic surgery.

[16]  Peter W. Hallinan Recognizing human eyes , 1991, Optics & Photonics.

[17]  Christian Küblbeck,et al.  Face detection and tracking in video sequences using the modifiedcensus transformation , 2006, Image Vis. Comput..

[18]  Roberto Valenti,et al.  Auto-Calibrated Gaze Estimation Using Human Gaze Patterns , 2017, International Journal of Computer Vision.

[19]  Peter Corcoran,et al.  A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms , 2017, IEEE Access.

[20]  Craig Hennessey,et al.  Long range eye tracking: bringing eye tracking into the living room , 2012, ETRA.

[21]  A. Naït-Ali,et al.  Performance of a Computer System for Recording and Analysing Eye Gaze Position Using an Infrared Light Device , 2003, Journal of Clinical Monitoring and Computing.

[22]  Margrit Betke,et al.  A Human–Computer Interface Using Symmetry Between Eyes to Detect Gaze Direction , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[23]  Haiying Wang,et al.  A Face Detection Method Combining Improved AdaBoost Algorithm and Template Matching in Video Sequence , 2016, 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC).

[24]  Bruno Oliveira Silvestre,et al.  An Evaluation Method of Research on Wearable Wireless Body Area Network in Healthcare , 2013 .

[25]  Du-Sik Park,et al.  3D user interface combining gaze and hand gestures for large-scale display , 2010, CHI EA '10.

[26]  Andrew T Duchowski,et al.  A breadth-first survey of eye-tracking applications , 2002, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[27]  Lijun Yin,et al.  Pointing with the eyes: Gaze estimation using a static/active camera system and 3D iris disk model , 2010, 2010 IEEE International Conference on Multimedia and Expo.

[28]  Jean-Philippe Thiran,et al.  A Regression-Based User Calibration Framework for Real-Time Gaze Estimation , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[29]  Andreas Bulling,et al.  EyeTab: model-based gaze estimation on unmodified tablet computers , 2014, ETRA.

[30]  Yambem Jina Chanu,et al.  Image Segmentation Using K -means Clustering Algorithm and Subtractive Clustering Algorithm , 2015 .

[31]  V. Vijayakumari,et al.  Face Recognition Techniques: A Survey , 2013, International Journal of Advanced Trends in Computer Science and Engineering.