Context-Aware Augmented Reality Using Human–Computer Interaction Models

作者：Ying Sun, Qiongqiong Guo, Shumei Zhao, Karthik Chandran, G. Fathima · 发表于：Journal of Control and Decision · 年份：2022 · DOI：10.1080/23307706.2022.2026260 · 被引用次数：22 · 研究领域：Augmented Reality Applications、Virtual Reality Applications and Impacts、Robotics and Automated Systems

Augmented Reality is a technique that allows users to overlap digital information with their physical world. The Augmented Reality (AR) displays have an exceptional characteristic from the Human–Computer Interaction (HCI) perspective. Due to its increasing popularity and application in diverse domains, increasing user-friendliness and AR usage are critical. Context-aware is one approach since an AR application can adapt to the user, environment, needs and enhance ergonomic principles and functionality. This paper proposes the Intelligent Contextaware Augmented Reality Model (ICAARM) for Human–Computer Interaction systems. This study explores and reduces interaction uncertainty by semantically modeling user-specific interaction with context, allowing personalised interaction. Sensory information is captured from an AR device to understand user interactions and context. These depictions carry semantics to Augmented Reality applications about the user's intention to interact with a specific device affordance. Thus, this study describes personalised gesture interaction in VR/AR applications for immersive/intelligent environments.