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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Ultrasound for Gaze Estimation
verfasst von : Andre Golard, Sachin S. Talathi
Erschienen in: Pattern Recognition. ICPR International Workshops and Challenges
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Abstract
Most eye tracking methods are light-based. As such they can suffer from ambient light changes when used outdoors. It has been suggested that ultrasound could provide a low power, fast, light-insensitive alternative to camera based sensors for eye tracking. We designed a bench top experimental setup to investigate the utility of ultrasound for eye tracking, and collected time of flight and amplitude data for a range of gaze angles of a model eye. We used this data as input for a machine learning model and demonstrate that we can effectively estimate gaze (gaze RMSE error of 1.021 ± 0.189\(^{\circ }\) with an adjusted \(R^{2}\) score of 89.92 ± 4.9).