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Appl. Sci. 2017, 7(5), 498; doi:10.3390/app7050498

Design of a Binocular Pupil and Gaze Point Detection System Utilizing High Definition Images

Department of Electrical and Electronics Engineering, Ankara University, Ankara 06830, Turkey
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Author to whom correspondence should be addressed.
Academic Editor: Ting-Chung Poon
Received: 1 March 2017 / Revised: 4 May 2017 / Accepted: 8 May 2017 / Published: 11 May 2017
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Abstract

This study proposes a novel binocular pupil and gaze detection system utilizing a remote full high definition (full HD) camera and employing LabVIEW. LabVIEW is inherently parallel and has fewer time-consuming algorithms. Many eye tracker applications are monocular and use low resolution cameras due to real-time image processing difficulties. We utilized the computer’s direct access memory channel for rapid data transmission and processed full HD images with LabVIEW. Full HD images make easier determinations of center coordinates/sizes of pupil and corneal reflection. We modified the camera so that the camera sensor passed only infrared (IR) images. Glints were taken as reference points for region of interest (ROI) area selection of the eye region in the face image. A morphologic filter was applied for erosion of noise, and a weighted average technique was used for center detection. To test system accuracy with 11 participants, we produced a visual stimulus set up to analyze each eye’s movement. Nonlinear mapping function was utilized for gaze estimation. Pupil size, pupil position, glint position and gaze point coordinates were obtained with free natural head movements in our system. This system also works at 2046 × 1086 resolution at 40 frames per second. It is assumed that 280 frames per second for 640 × 480 pixel images is the case. Experimental results show that the average gaze detection error for 11 participants was 0.76° for the left eye, 0.89° for right eye and 0.83° for the mean of two eyes. View Full-Text
Keywords: eye tracker; binocular pupil detection; gaze point; LabVIEW eye tracker; binocular pupil detection; gaze point; LabVIEW
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Durna, Y.; Ari, F. Design of a Binocular Pupil and Gaze Point Detection System Utilizing High Definition Images. Appl. Sci. 2017, 7, 498.

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