AI-Driven Responsive GUI for XR: Context-Aware Visual Adaptation
Resumo
Augmented Reality enhances a user’s perception of the real world by overlaying digital information onto the physical environment in real time. One common means of interaction within AR is through Graphical User Interfaces, however, these interfaces can inadvertently occlude important elements of the physical scene. Although window repositioning is straightforward in traditional 2D interfaces, spatial placement in 3D AR environments is more complex, as it must consider factors such as user position, viewing direction, and contextual relevance. This work proposes an approach for the automatic positioning and coloring of GUI elements in AR, enabling interactive panels to dynamically adapt to environmental and contextual conditions. The system adjusts interface placement and appearance in real time based on contextual cues, such as object detection, human presence, and lighting changes. To accomplish this, computer vision techniques are employed to identify and classify objects, while generative AI models interpret high-level contextual information. This enables the interface to reposition itself to avoid occlusions and adjust visual properties, such as color and contrast, for optimal legibility and user comfort. The design and refinement of the system were guided by iterative user testing to ensure usability and effectiveness.
Palavras-chave:
Augmented Reality, Graphical User Interfaces, User Interaction, Automatic User Interface Placement, Context-Aware Extended Reality
Referências
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K. Todi and T. R. Jonker. A framework for computational design and adaptation of extended reality user interfaces. Available [link], 2023. Also at [link]
F. Paterno. User interface design adaptation. In The Encyclopedia of Human-Computer Interaction, 2nd ed. K. Madsen, Ed. Interaction Design Foundation, 2024. Accessed Sep. 17, 2024.
J. Grubert, T. Langlotz, S. Zollmann, and H. Regenbrecht. Towards pervasive augmented reality Context-awareness in augmented reality. IEEE Transactions on Visualization and Computer Graphics, 23(6):1706–1724, 2017.
Z. Stefanidi, G. Margetis, S. Ntoa, and G. Papagiannakis. Real-time adaptation of context-aware intelligent user interfaces for enhanced situational awareness. IEEE Access, 10:23367–23393, 2022.
F. Lu, M. Chen, H. Hsu, P. Deshpande, C. Y. Wang, and B. MacIntyre. Adaptive 3D UI placement in mixed reality using deep reinforcement learning. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24). Association for Computing Machinery, New York, 2024. Available DOI: 10.1145/3613905.3651059
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OpenAI. ChatGPT. Available [link], 2024.
C.-Y. Wang, I.-H. Yeh, and H.-Y. M. Liao. YOLOv9 Learning what you want to learn using programmable gradient information. arXiv preprint arXiv:2402.13616, 2024. Accessed Sept. 18, 2024.
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Apple Inc. Introducing Apple Vision Pro. Available [link], 2023. Accessed 2025-06-21.
Unity Technologies. AsyncGPURReadbackRequest and EncodeToPNG. Unity Discussions, Sep. 2018. Available [link]
S. Liu, P. Lai, D. Tian, and C.-W. Chen. New depth coding techniques with utilization of corresponding video. In Proc. 3DTV Conference, 551–561, 2011.
Black Technology LTD. Living room with people using VR and anchor art. Stable Diffusion, 2024. Available [link]
Publicado
30/09/2025
Como Citar
SANTOS, André Corrêa; BARÃO, Pedro Bittar; LIMA, Rafael Melhado Araujo; SOARES, Luciano Pereira.
AI-Driven Responsive GUI for XR: Context-Aware Visual Adaptation. In: SIMPÓSIO DE REALIDADE VIRTUAL E AUMENTADA (SVR), 27. , 2025, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 273-282.
