Human–System Interaction Based on Eye Tracking for a Virtual Workshop

Zenggui Gao, Jiaying Li, Mengyao Dong, Ruining Yang and Lilan Liu
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Zenggui Gao: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Jiaying Li: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Mengyao Dong: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Ruining Yang: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Lilan Liu: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China

Sustainability, 2022, vol. 14, issue 11, 1-18

Abstract: With the constant exploration and development of intelligent manufacturing, the concept of digital twins has been proposed and applied. In view of the complexity and intellectualization of virtual workshop systems, real workshops can link with virtual workshosp based on AR under the structure of digital twins, which allows users to interact with virtual information and perceive the virtual information superimposed on the real world with great immersion. However, the three-dimensionality of virtual workshops and interaction with complex workshop information can be challenging for users. Due to a shortage of input bandwidth and the nontraditional mode of interaction, a more natural interaction technique for virtual workshops is required. To solve such problems, this paper presents a technical framework for 3D eye movement interaction applied to a virtual workshop. An eye movement interaction technique, oriented to implicit interaction and explicit interaction, is developed by establishing behavior recognition and interaction intention understanding. An eye-movement experiment verifies the former’s accuracy is above 90% and had better recognition performance. A better feature vector group of the latter is selected to establish a model and verify its feasibility and effectiveness. Finally, the feasibility of the framework is verified through the development of an application example.

Keywords: eye movement behavior recognition; intention understanding; eye movement interaction; virtual workshop (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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