Blinking supervision in a working environment

Abstract

The health of the ocular surface requires blinks of the eye to be frequent in order to provide moisture and to renew the tear film. However, blinking frequency has been shown to decrease in certain conditions, such as when subjects are conducting tasks with high cognitive and visual demands. These conditions are becoming more common as people work or spend their leisure time in front of video display terminals (VDT). Supervision of blinking frequency in such environments is possible thanks to the availability of computer-integrated cameras. Therefore, the aim of the present study is to develop an algorithm for the detection of eye blinks and to test it, in a number of videos captured, while subjects are conducting a variety of tasks in front of the computer. The sensitivity of the algorithm for blink detection was found to be of 87.54% (range 30-100%), with a mean false positive rate of 0.19% (range 0-1.7%), depending on the illumination conditions during which the image was captured and other computer-user spacial configurations. The current automatic process is based on a partly modified preexisting eye detection and image processing algorithms and consists of 4 stages that are aimed at eye detection, eye tracking, iris detection and segmentation and iris height/width ratio assessment.

Blinking characterization from high speed video records. Application to biometric authentication

“…Environmental conditions, age and gender variations in blink rate have been reported [ 8 – 11 ]. In healthy subjects, blinking frequency decrease when subjects are conducting tasks with high cognitive and visual demands [ 12 , 13 ]. Esteban [ 14 ] asserted the blink reflex evaluation as an essential tool for the diagnosis and pathophysiological insight into an important number of human neurological disorders.…”

“…Traditionally, the eye blink was assessed by procedures requiring the application of electrodes to monitor the OO electromyographic activity and get the EOG signal [ 20 – 26 ], or the use of direct magnetic search coil technique [ 27 – 30 ]. Nevertheless, contact-free recording procedures such as photo or video, that permit a quantitative assessment for eye movement during blinking without interfering with the subject, have also been used [ 2 , 3 , 13 , 17 , 18 , 31 – 47 ].…”

Eye Tracking Algorithm Based on Multi Model Kalman Filter

“…The main weaknesses of this method are inefficiency in the presence of the hair in the front part of the eye and face direction. In Morcego et al (2016) [11], a method is proposed for estimating the parameters of the eye and tracking it. In this method, the eye model should be designed first.…”

Estudi del parpelleig en usuaris/es de pantalles digitals : anàlisi d'estratègies pel condicionament del parpelleig i la distància de manera no intrusiva

“…L'algorisme implementat realitza en un primer pas la detecció de l'ull, posteriorment fa el seguiment de l'ull detectat i, finalment, permet el comptatge del parpelleig enregistrant en quin frame té lloc el mateix, per tal de poder mesurar posteriorment la seva regularitat. Descrivim breument els principis en què es basen cada una de les tres etapes de l'algorisme [Morcego et al, 2016]. li assigna el valor de la suma de tots els píxels col!locats en la regió superior esquerra de la imatge original (en relació a la posició de l'element).…”

“…Novament les eines proporcionades per la Toolbox de Visió per Computador de Matlab ® van permetre implementar més àgilment aquest algorisme KLT de seguiment en l'aplicació de detecció del parpelleig. La FIGURA 6.2 mostra el correcte seguiment de l'ull esquerre durant el transcurs de diferents frames [Cabrerizo, 2014;Morcego et al, 2016].…”