Abstract
Due to the limitations of gaze detection based on one eye, binocular gaze detection using the gaze positions of both eyes has been researched. Most previous binocular gaze detection research calculated a gaze position as the simple average position of the detected gaze points of both eyes. To improve this approach, we propose a new binocular gaze detection method using a fuzzy algorithm with quality measurement of both eyes. The proposed method is used in the following three ways. First, in order to combine the gaze points of the left and right eyes, we measure four qualities on both eyes: distortion by an eyelid, distortion by the specular reflection (SR), the level of circularity of the pupil, and the distance between the pupil boundary and the SR center. Second, in order to obtain a more accurate pupil boundary, we compensate the distorted boundary of a pupil by an eyelid based on information from the lower half-circle of the pupil. Third, the final gaze position is calculated using a fuzzy algorithm based on four quality-measured scores. Experimental results show that the root-mean-square error of gaze estimation by the proposed method is approximately 0.67518 deg.
Highlights
Gaze detection is a method of detecting where a user is looking
We proposed a new binocular gaze detection method using a fuzzy algorithm with a quality measurement of both eyes
To combine the gaze points of the left and right eyes, we measured the qualities of both eyes based on the distortion from an eyelid and the specular reflection (SR), the level of pupil circularity, and the distance between the pupil boundary and the SR center
Summary
Gaze detection is a method of detecting where a user is looking. Previous gaze detection methods can be categorized into two types: monocular and binocular gaze detection methods. Murphy-Chutorian et al proposed a gaze detection method for driver monitoring.[4] these methods are limited in that they require a complex calibration procedure for multiple cameras or result in low accuracy In another approach to monocular gaze detection, methods in which a gaze position is estimated using a wearable head-mounted device with a camera[5] and near infrared (NIR) illuminators have been proposed.[6,7,8,9] Piccardi et al used a single head-mounted camera for calculating gaze positions.[5] Ko et al proposed a gaze detection method using four NIR illuminators attached to the four corners of a monitor and a helmet-type device with a single eye-capturing camera.[8] wearing additional equipment can be uncomfortable for users. Binocular gaze detection using the gaze positions of both eyes has been proposed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
