A miniature head-mounted camera for measuring eye closure

Authors:
Simon J. Knopp;Philip J. Bones;Stephen J. Weddell;Carrie R. H. Innes;Richard D. Jones
Affiliations:
University of Canterbury;University of Canterbury;University of Canterbury;NZ Brain Research Institute;University of Canterbury
Venue:
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Year:
2012

Citing 5
Cited 0

Real-time eye, gaze, and face pose tracking for monitoring driver vigilance

Real-Time Imaging
Building a lightweight eyetracking headgear

Proceedings of the 2004 symposium on Eye tracking research & applications
Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Robust real-time pupil tracking in highly off-axis images

Proceedings of the Symposium on Eye Tracking Research and Applications
How iris recognition works

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a miniature camera module for capturing close-up video of one eye and the image processing steps to locate the pupil and measure eye closure from this video. This camera is one component of a multi-sensory device for measuring drowsiness and detecting complete momentary lapses of responsiveness. We describe a flood-fill-based algorithm for locating the pupil and shape-based criteria for determining whether the pupil is partly covered by the eyelid. Percentage eye closure (PERCLOS) is implemented as an example of a meaningful measurement that can be derived from this extracted pupil data. Preliminary results show that the algorithm produces output very close to that obtained by manual frame-by-frame classification of the eye video.