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Sensors 2017, 17(1), 41;

Multi-User Identification-Based Eye-Tracking Algorithm Using Position Estimation

Department of Electronic Engineering, Sogang University, Seoul 04107, Korea
Academic Editor: Joonki Paik
Received: 13 December 2016 / Revised: 22 December 2016 / Accepted: 23 December 2016 / Published: 27 December 2016
(This article belongs to the Special Issue Video Analysis and Tracking Using State-of-the-Art Sensors)
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This paper proposes a new multi-user eye-tracking algorithm using position estimation. Conventional eye-tracking algorithms are typically suitable only for a single user, and thereby cannot be used for a multi-user system. Even though they can be used to track the eyes of multiple users, their detection accuracy is low and they cannot identify multiple users individually. The proposed algorithm solves these problems and enhances the detection accuracy. Specifically, the proposed algorithm adopts a classifier to detect faces for the red, green, and blue (RGB) and depth images. Then, it calculates features based on the histogram of the oriented gradient for the detected facial region to identify multiple users, and selects the template that best matches the users from a pre-determined face database. Finally, the proposed algorithm extracts the final eye positions based on anatomical proportions. Simulation results show that the proposed algorithm improved the average F1 score by up to 0.490, compared with benchmark algorithms. View Full-Text
Keywords: eye tracking; face detection; multi-user identification eye tracking; face detection; multi-user identification

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Kang, S.-J. Multi-User Identification-Based Eye-Tracking Algorithm Using Position Estimation. Sensors 2017, 17, 41.

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