Probabilistic approach to robust wearable gaze tracking
This paper presents a method for computing the gaze point using camera data captured with a wearable gaze tracking device. The method utilizes a physical model of the human eye, advanced Bayesian computer vision algorithms, and Kalman filtering, resulting in high accuracy and low noise. Our C++ impl...
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| Main Authors: | Miika Toivanen, Kristian Lukander, Kai Puolamäki |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-11-01
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| Series: | Journal of Eye Movement Research |
| Subjects: | |
| Online Access: | https://bop.unibe.ch/JEMR/article/view/3792 |
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