Realtime computer interaction via eye tracking
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Through eye tracking technology, scientists have explored the eyes diverse aspects and capabilities. There are many potential applications that benefit from eye tracking. Each benefit from advances in computer technology as this results in improved quality and decreased costs for eye-tracking systems.This thesis presents a computer vision-based eye tracking system for human computer interaction. The eye tracking system allows the user to indicate a region of interest in a large data space and to magnify that area, without using traditional pointer devices. Presented is an iris tracking algorithm adapted from Camshift; an algorithm originally designed for face or hand tracking. Although the iris is much smaller and highly dynamic. the modified Camshift algorithm efficiently tracks the iris in real-time. Also presented is a method to map the iris centroid, in video coordinates to screen coordinates; and two novel calibration techniques, four point and one-point calibration. Results presented show that the accuracy for the proposed one-point calibration technique exceeds the accuracy obtained from calibrating with four points. The innovation behind the one-point calibration comes from using observed eye scanning behaviour to constrain the calibration process. Lastly, the thesis proposes a non-linear visualisation as an eye-tracking application, along with an implementation.
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