Emerging Augmented Reality (AR) technologies offer immersive, spatially anchored interfaces that can transform remote collaboration beyond the limitations of traditional 2D video conferencing. In this work, we introduce a task-agnostic AR system that dynamically adapts the placement of virtual elements and visual guidance cues based on real-time user interaction context and avatar behavior. Unlike prior approaches that statically anchor content to fixed locations or rely on manual placement, our framework continuously evaluates a sliding window of user focus and applies a multi-objective optimization, balancing proximity, visual attention, and collaboration context, to reposition interface elements. We evaluated our system on two representative tasks (problem solving and knowledge-work) with 10 participants, comparing four placement strategies (random, proximity-based, individual action-based, group action-based). Quantitative results show that our action grouping method reduces task completion time by up to 20 % and gives higher subjective ratings of focus and usability. Qualitative feedback further underscores the importance of low-frequency repositioning and context-aware grouping to minimize distraction. These findings demonstrate that adaptive AR interfaces can significantly enhance collaborative efficiency and user satisfaction, suggesting a new direction for context-driven UI in mixed reality environments.

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Adaptive Interface Improving User Focus in Collaborative AR Systems

  • Robin Fischer,
  • Benedictus Kent Chandra,
  • Shiann-Jang Wang,
  • Wei-En Hsu,
  • Li-Chen Fu

摘要

Emerging Augmented Reality (AR) technologies offer immersive, spatially anchored interfaces that can transform remote collaboration beyond the limitations of traditional 2D video conferencing. In this work, we introduce a task-agnostic AR system that dynamically adapts the placement of virtual elements and visual guidance cues based on real-time user interaction context and avatar behavior. Unlike prior approaches that statically anchor content to fixed locations or rely on manual placement, our framework continuously evaluates a sliding window of user focus and applies a multi-objective optimization, balancing proximity, visual attention, and collaboration context, to reposition interface elements. We evaluated our system on two representative tasks (problem solving and knowledge-work) with 10 participants, comparing four placement strategies (random, proximity-based, individual action-based, group action-based). Quantitative results show that our action grouping method reduces task completion time by up to 20 % and gives higher subjective ratings of focus and usability. Qualitative feedback further underscores the importance of low-frequency repositioning and context-aware grouping to minimize distraction. These findings demonstrate that adaptive AR interfaces can significantly enhance collaborative efficiency and user satisfaction, suggesting a new direction for context-driven UI in mixed reality environments.