Automated eye blink detection and tracking using template matching

Awais, Muhammad ORCID: https://orcid.org/0000-0001-6421-9245, Badruddin, Nasreen and Drieberg, Micheal (2013) Automated eye blink detection and tracking using template matching. In: 2013 IEEE Student Conference on Research and Developement. The Institute of Electrical and Electronics Engineers (IEEE). ISBN 9781479926565

Full text not available from this repository. (Request a copy)

Abstract

Eye blink detection is considered to be one of the most reliable sources of communication in modern human computer interaction (HCI) systems. This paper proposes a new method for eye blink detection using template matching and similarity measure. In order to minimize the false detection due to changing background in the video frame, face detection is applied before extraction of the eye template. Golden ratio concept is introduced for robust eye detection and is followed by eye template creation for tracking. Eye tracking is performed by template matching between template image and surrounding region. The normalized correlation coefficient is computed for successful eye tracking. Eye blink detection is performed based upon the correlation score as the score changes significantly whenever a blink occurs. The proposed system provides an overall precision of 92.8% and overall accuracy of 99.6% with 0.1% false positive rate in different experimental conditions.

Item Type:	Book Section
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and AI
Depositing User:	LivePure Connector
Date Deposited:	17 Oct 2023 00:48
Last Modified:	10 Dec 2024 01:13
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93329
DOI:	10.1109/scored.2013.7002546

Actions (login required)

View Item