FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
A software framework for simulating eye trackers
Proceedings of the 2008 symposium on Eye tracking research & applications
Taxonomic study of polynomial regressions applied to the calibration of video-oculographic systems
Proceedings of the 2008 symposium on Eye tracking research & applications
A neural-based remote eye gaze tracker under natural head motion
Computer Methods and Programs in Biomedicine
In the Eye of the Beholder: A Survey of Models for Eyes and Gaze
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Novel Simple 2D Model of Eye Gaze Estimation
IHMSC '10 Proceedings of the 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 01
Topography-Based Detection of the Iris Centre Using Multiple-Resolution Images
IMVIP '11 Proceedings of the 2011 Irish Machine Vision and Image Processing Conference
Proceedings of the 2013 international conference on Intelligent user interfaces
SideWays: a gaze interface for spontaneous interaction with situated displays
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
| Hi-index | 0.00 |
Low cost eye tracking is an actual challenging research topic for the eye tracking community. Gaze tracking based on a web cam and without infrared light is a searched goal to broaden the applications of eye tracking systems. Web cam based eye tracking results in new challenges to solve such as a wider field of view and a lower image quality. In addition, no infrared light implies that glints cannot be used anymore as a tracking feature. In this paper, a thorough study has been carried out to evaluate pupil (iris) center-eye corner (PC-EC) vector as feature for gaze estimation based on interpolation methods in low cost eye tracking, as it is considered to be partially equivalent to the pupil center-corneal reflection (PC-CR) vector. The analysis is carried out both based on simulated and real data. The experiments show that eye corner positions in the image move slightly when the user is looking at different points of the screen, even with a static head position. This lowers the possible accuracy of the gaze estimation, significantly reducing the accuracy of the system under standard working conditions to 2--3 degrees.