Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21605-3_20 | HCI (2) |
Keywords | Field | DocType |
natural light,conventional method,eye-gaze detection,vertical eye-gaze detection,horizontal eye-gaze,limbus tracking method,eye-gaze input system,new method,practical eye-gaze input system,new eye-gaze detection method,horizontal eye-gaze detection,image analysis,vertical eye-gaze | Computer vision,Computer science,Vertical direction,Personal computer,Eye tracking,Artificial intelligence,Video camera | Conference |
Volume | ISSN | Citations |
6762 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kiyohiko Abe | 1 | 14 | 4.66 |
| Shoichi Ohi | 2 | 14 | 3.65 |
| Minoru Ohyama | 3 | 33 | 9.48 |