Fast Eye Tracking and Feature Measurement using a Multi-stage Particle Filter

Radu Danescu, Adrian Sergiu Darabant, Diana Borza

2017

Abstract

Eye trackers – systems that measure the activity of the eyes – are nowadays used in creative ways into a variety of domains: medicine, psychology, automotive industry, marketing etc. This paper presents a real time method for tracking and measuring eye features (iris position, eye contour, blinks) in video frames based on particle filters. We propose a coarse-to-fine approach to solve the eye tracking problem: a first particle filter is used to roughly estimate the position of the iris centers. Next, this estimate is analysed to decide the state of the eyes: opened or half-opened/closed. If the eyes are opened, two independent particles filters are used to determine the contour of each eye. Our algorithm takes less than 11 milliseconds on a regular PC.

Paper Citation

in Harvard Style

Danescu R., Sergiu Darabant A. and Borza D. (2017). Fast Eye Tracking and Feature Measurement using a Multi-stage Particle Filter . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-226-4, pages 258-265. DOI: 10.5220/0006130202580265

in Bibtex Style

@conference{visapp17,
author={Radu Danescu and Adrian Sergiu Darabant and Diana Borza},
title={Fast Eye Tracking and Feature Measurement using a Multi-stage Particle Filter},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={258-265},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006130202580265},
isbn={978-989-758-226-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)
TI - Fast Eye Tracking and Feature Measurement using a Multi-stage Particle Filter
SN - 978-989-758-226-4
AU - Danescu R.
AU - Sergiu Darabant A.
AU - Borza D.
PY - 2017
SP - 258
EP - 265
DO - 10.5220/0006130202580265