Eye Tracking as a Method of Controlling Applications on Mobile Devices

The possibility of using eye tracking in multimodal interaction is discussed. Nowadays, communication by eye movements can be both natural and intuitive. The main goal of the present work was to develop a method which allows for controlling a smartphone application by using eye movements. The designed software was based on the Open Source Computer Vision Library (OpenCV) and dedicated for Android system. We conducted two sets of tests: usability tests of the new solution, and tests on how the methods of template matching affect the operation of the device. The results, obtained by testing a small group of people, showed that the application meets all stated expectations.

[1]  David M. W. Powers,et al.  Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation , 2011, ArXiv.

[2]  Miad Faezipour,et al.  Eye Tracking and Head Movement Detection: A State-of-Art Survey , 2013, IEEE Journal of Translational Engineering in Health and Medicine.

[3]  L. Young,et al.  Survey of eye movement recording methods , 1975 .

[4]  Wojciech Matusik,et al.  Eye Tracking for Everyone , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[6]  Nicu Sebe,et al.  Multimodal Human Computer Interaction , 2005 .

[7]  Hari Singh Dhillon,et al.  Human Eye Tracking and Related Issues: A Review , 2012 .

[8]  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.

[9]  Pawel Strumillo,et al.  A vision-based head movement tracking system for human-computer interfacing , 2012, 2012 Joint Conference New Trends In Audio & Video And Signal Processing: Algorithms, Architectures, Arrangements And Applications (NTAV/SPA).

[10]  Jean Meunier,et al.  3D head tracking for fall detection using a single calibrated camera , 2013, Image Vis. Comput..

[11]  Nicu Sebe,et al.  Multimodal Human Computer Interaction: A Survey , 2005, ICCV-HCI.