Abstract
Gaze tracking is a camera-vision based technology for identifying the location where a user is looking. In general, a calibration process is applied at the initial stage of most gaze tracking systems. This process is necessary to calibrate for the differences in the eyeballs and cornea size of the user, as well as the angle kappa, and to find the relationship between the user’s eye and screen coordinates. It is applied on the basis of the information of the user’s pupil and corneal specular reflection obtained while the user is looking at several predetermined positions on a screen. In previous studies, user calibration was performed using various types of markers and marker display methods. However, studies on estimating the accuracy of gaze detection through the results obtained during the calibration process have yet to be carried out. Therefore, we propose the method for estimating the accuracy of a final gaze tracking system with a near-infrared (NIR) camera by using a fuzzy system based on the user calibration information. Here, the accuracy of the final gaze tracking system ensures the gaze detection accuracy during the testing stage of the gaze tracking system. Experiments were performed using a total of four types of markers and three types of marker display methods. From them, it was found that the proposed method correctly estimated the accuracy of the gaze tracking regardless of the various marker and marker display types applied.
Highlights
Studies have been actively carried out to accurately calculate a user’s gaze location based on the movement of their face or eyes [1,2]
The Euclidean distance is calculated between the user’s calculated gaze and the reference positions obtained during the user calibration
A 700-nm long pass filter (Kodak Wratten Filter No 89B, Rochester, NY, USA [30]) and a zoom lens were mounted on a webcam (Logitech C600, Lausanne, Switzerland [31]) having a universal serial bus (USB) interface
Summary
Studies have been actively carried out to accurately calculate a user’s gaze location based on the movement of their face or eyes [1,2]. To achieve a gaze tracking system with high accuracy, an accurate user calibration process is as important as the accurate detection of the user’s pupil center and reflection. If the calibration process is accurate, an accurate gaze tracking can be achieved Past studies in this area can be mainly divided into two types: utilizing the estimation model of a user-calibration based gaze tracking result and not utilizing such a model. When the movements of the marker are complex, the user must spend more time training in advance, thereby leading to a decline in user convenience In these previous studies, a user calibration was conducted by applying various types of markers and marker display methods.
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