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| Content Provider | ACM Digital Library |
|---|---|
| Author | Wang, Tianyu Miluzzo, Emiliano Campbell, Andrew T. |
| Abstract | As smartphones evolve researchers are studying new techniques to ease the human-mobile interaction. We propose EyePhone, a novel "hand-free" interfacing system capable of driving mobile applications/functions using only the user's eyes movement and actions (e.g., wink). EyePhone tracks the user's eye movement across the phone's display using the camera mounted on the front of the phone; more specifically, machine learning algorithms are used to: i) track the eye and infer its position on the mobile phone display as a user views a particular application; and ii) detect eye blinks that emulate mouse clicks to activate the target application under view. We present a prototype implementation of EyePhone on a Nokia N810, which is capable of tracking the position of the eye on the display, mapping this positions to an application that is activated by a wink. At no time does the user have to physically touch the phone display. |
| Starting Page | 15 |
| Ending Page | 20 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450301978 |
| DOI | 10.1145/1851322.1851328 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-08-30 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Human-phone interaction Mobile sensing systems Machine learning Mobile phones |
| Content Type | Text |
| Resource Type | Article |
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