Abstract
Gaze tracking technologies provide an unconventional way of human–computer interaction, envisaged to advance practical applications and industrial products in a multitude of fields. The success of such systems depends on selecting the best calibration setup and image features that correspond to a person׳s line of sight. The purpose of this study is to estimate eye gaze from a single, low cost web-cam, under natural lighting. Facial traits are extracted from the sensory data, from which distance vectors related to gaze are derived. Different experimental setups are studied to evaluate the robustness of the proposed method with respect to various calibration setups, camera position and head movements. The use of new additional features improves the modeling of the subtle eye movements in the vertical direction, while a new calibration setup is proposed that further enhances the performance. The results demonstrate that the proposed framework is able to track gaze with good accuracy, consolidating the use of inexpensive equipment and techniques towards an ever-expanding range of gaze tracking applications.
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.
