A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
EyeKeys: A Real-Time Vision Interface Based on Gaze Detection from a Low-Grade Video Camera
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 10 - Volume 10
Computer Vision Syndrome: A widely spreading but largely unknown epidemic among computer users
Computers in Human Behavior
EyePhone: activating mobile phones with your eyes
Proceedings of the second ACM SIGCOMM workshop on Networking, systems, and applications on mobile handhelds
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
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Computer Vision Syndrome (CVS) is a common problem in the "Information Age", and it is becoming more serious as mobile devices (e.g. smartphones and tablet PCs) with small, low-resolution screens are outnumbering the home computers. The simplest way to avoid CVS is to blink frequently. However, most people do not realize that they blink less and some do not blink at all in front of the screen. In this paper, we present a mobile application that keeps track of the reader's blink rate and prods the user to blink if an exceptionally low blink rate is detected. The proposed eye detection and tracking algorithm is designed for mobile devices and can keep track of the eyes in spite of camera motion. The main idea is to predict the eye position in the camera frame using the feedback from the built-in accelerometer. The eye tracking system was built on a commercial Tablet PC. The experimental results consistently show that the scheme can withstand very aggressive mobility scenarios.