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Eye control system based on convolutional neural network: a review

Jianbin Xiong (School of Automation, Guangdong Polytechnic Normal University, Guangzhou, China, and)
Jinji Nie (School of Automation, Guangdong Polytechnic Normal University, Guangzhou, China, and)
Jiehao Li (College of Engineering, South China Agricultural University, Guangzhou, China)

Assembly Automation

ISSN: 0144-5154

Article publication date: 29 August 2022

Issue publication date: 17 October 2022

284

Abstract

Purpose

This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based on CNNs is helpful for future research.

Design/methodology/approach

In this paper, first, it covers the fundamentals of the eye control system as well as the fundamentals of CNNs. Second, the standard CNN model and the target detection model are summarized. The eye control system’s CNN gaze estimation approach and model are next described and summarized. Finally, the progress of the gaze estimation of the eye control system is discussed and anticipated.

Findings

The eye control system accomplishes the control effect using gaze estimation technology, which focuses on the features and information of the eyeball, eye movement and gaze, among other things. The traditional eye control system adopts pupil monitoring, pupil positioning, Hough algorithm and other methods. This study will focus on a CNN-based eye control system. First of all, the authors present the CNN model, which is effective in image identification, target detection and tracking. Furthermore, the CNN-based eye control system is separated into three categories: semantic information, monocular/binocular and full-face. Finally, three challenges linked to the development of an eye control system based on a CNN are discussed, along with possible solutions.

Originality/value

This research can provide theoretical and engineering basis for the eye control system platform. In addition, it also summarizes the ideas of predecessors to support the development of future research.

Keywords

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant no. 62073090, 61473331, in part by the Natural Science Foundation of Guangdong Province of China under Grant no. 2019A1515010700, in part by the Key (natural) Project of Guangdong Provincial under Grant no. 2019KZDXM020, 2019KZDZX1004, 2019KZDZX1042, in part by Special projects in key areas of ordinary colleges and universities in Guangdong Province no. 2020ZDZX2014, 2020KCXTD017, in part by the Introduction of Talents Project of Guangdong Polytechnic Normal University of China under Grant no. 991512203, 991560236.

Citation

Xiong, J., Nie, J. and Li, J. (2022), "Eye control system based on convolutional neural network: a review", Assembly Automation, Vol. 42 No. 5, pp. 595-615. https://doi.org/10.1108/AA-02-2022-0030

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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