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.

翻译：近年来，增强现实（AR）研究的发展突显了情境感知在提升界面效能与用户体验中的关键作用。这强调了智能增强现实（iAR）界面的必要性，此类界面需能动态适应不同情境以提供最优体验。本文中，我们（a）提出了一个用于iAR中情境感知推理与适配的综合框架；（b）引入了一种通过可量化输入数据描述情境的分类法；以及（c）提出了一种架构，概述了如何在iAR中实现我们提出的框架与分类法。此外，我们设计了一项实证AR实验，以观察用户行为，并在情境切换场景中记录用户表现、情境及用户对AR界面的指定适配。我们（d）探讨了该场景中情境与用户适配之间的细致关联，并讨论了本框架在识别这些模式方面的重要性。该实验强调了情境感知在iAR中的重要意义，并为此特定场景提供了初步的训练数据集。