Towards Intelligent Augmented Reality (iAR): A Taxonomy of Context, an Architecture for iAR, and an Empirical Study

TL;DR

A comprehensive framework for context-aware inference and adaptation in iAR is proposed, a taxonomy that describes context through quantifiable input data is introduced, and an architecture is presented that outlines the implementation of the proposed framework and taxonomy within iAR.

Abstract

Recent advancements in Augmented Reality (AR) research have highlighted the critical role of context awareness in enhancing interface effectiveness and user experience. This underscores the need for intelligent AR (iAR) interfaces that dynamically adapt across various contexts to provide optimal experiences. In this paper, we (a) propose a comprehensive framework for context-aware inference and adaptation in iAR, (b) introduce a taxonomy that describes context through quantifiable input data, and (c) present an architecture that outlines the implementation of our proposed framework and taxonomy within iAR. Additionally, we present an empirical AR experiment to observe user behavior and record user performance, context, and user-specified adaptations to the AR interfaces within a context-switching scenario. We (d) explore the nuanced relationships between context and user adaptations in this scenario and discuss the significance of our framework in identifying these patterns. This experiment emphasizes the significance of context-awareness in iAR and provides a preliminary training dataset for this specific Scenario.

Figures (9)

• Figure 1: Intelligent AR interfaces adapt the interface based on quantifiable input data from the user, sensors, and personal or publicly available data storage and databases.
• Figure 2: Our framework for Context-aware Inference and Adaptation using our taxonomy of Context.
• Figure 3: Persistent and transient context components provide the iAR with information about the user profile and state.
• Figure 4: Persistent and Transient context components present: (a): the structure and state of physical items and phenomena in the user's local and immediate environment. (b): public/global information and the hardware and firmware state and capabilities of the AR and available digital devices. Transient context components present: (c): accessible information from the profile and state of physical/virtual attendees in the current context and their interactions with the real-world/digital setting. (d): the connections and interactions of the user's profile and state with their social, real-world, and digital setting.
• Figure 5: The architecture of intelligent AR systems.