Abstract
The presence of saccadic and smooth movements in the eye makes modular neural networks composed of two experts, each individually responsible for saccadic and smooth movements of the eyes, well suited for the tracking of human point-of-regard. To establish a basis for comparison on our data, we also consider a scalar ARMA model and a (vector) state space model. The purpose of this analysis is to build a reasonable model of human eye motion to use in prediction of point-of-regard. The ability to predict the point-of-regard of a human subject has applications in eye-tracking for man-machine interfacing, vigilance detection, and as a tool in cognitive psychology.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
