Abstract

Eye gaze control is playing an important role in AR system. However, the physiology mechanism of eye gaze control can’t be totally understood for the limitation of biomedicine presently. The research on evolving networks has been widely studied recently and the degree distributions of these networks are of a power-law form. To enhance the calibration accuracy and improve the judgment effects of gazing objects, in this paper, the property of eye gaze tracking network is studied according to those methods used in complex network. The eye gaze tracking network model inserted position information and achievement probability was established and the degree distribution was discussed. Simulation results show that the degree distribution of eye gaze tracking network is scale-free.

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 call

Disclaimer: 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.