We have developed an eye-gaze input system for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS). The system utilizes a personal computer and a home video camera to detect eye-gaze under natural light. Our practical eye-gaze input system is capable of classifying the horizontal eye-gaze of users with a high degree of accuracy. However, it can only detect three directions of vertical eye-gaze. If the detection resolution in the vertical direction is increased, more indicators will be displayed on the screen. To increase the resolution of vertical eye-gaze detection, we apply a limbus tracking method, which is also the conventional method used for horizontal eye-gaze detection. In this paper, we present a new eye-gaze detection method by image analysis using the limbus tracking method. We also report the experimental results of our new method. © 2011 Springer-Verlag.
CITATION STYLE
Abe, K., Ohi, S., & Ohyama, M. (2011). Eye-gaze detection by image analysis under natural light. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6762 LNCS, pp. 176–184). https://doi.org/10.1007/978-3-642-21605-3_20
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