Estimation of Gaze Detection Accuracy Using the Calibration Information-Based Fuzzy System
AbstractGaze 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. View Full-Text
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Gwon, S.Y.; Jung, D.; Pan, W.; Park, K.R. Estimation of Gaze Detection Accuracy Using the Calibration Information-Based Fuzzy System. Sensors 2016, 16, 60.
Gwon SY, Jung D, Pan W, Park KR. Estimation of Gaze Detection Accuracy Using the Calibration Information-Based Fuzzy System. Sensors. 2016; 16(1):60.Chicago/Turabian Style
Gwon, Su Y.; Jung, Dongwook; Pan, Weiyuan; Park, Kang R. 2016. "Estimation of Gaze Detection Accuracy Using the Calibration Information-Based Fuzzy System." Sensors 16, no. 1: 60.
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