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Investigating the Design Considerations for Integrating Text-to-Image Generative AI within Augmented Reality Environments

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arxiv 2303.16593 v2 pith:K5MDFEWT submitted 2023-03-29 cs.HC

Yongquan Hu , Dawen Zhang , Mingyue Yuan , Kaiqi Xian , Don Samitha Elvitigala , June Kim , Gelareh Mohammadi , Zhenchang Xing
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Xiwei Xu Aaron Quigley
This is my paper · ORCID
classification cs.HC
keywords designgenaiapplicationartificialaugmentedcontentgenerativeinsights
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Generative Artificial Intelligence (GenAI) has emerged as a fundamental component of intelligent interactive systems, enabling the automatic generation of multimodal media content. The continuous enhancement in the quality of Artificial Intelligence-Generated Content (AIGC), including but not limited to images and text, is forging new paradigms for its application, particularly within the domain of Augmented Reality (AR). Nevertheless, the application of GenAI within the AR design process remains opaque. This paper aims to articulate a design space encapsulating a series of criteria and a prototypical process to aid practitioners in assessing the aptness of adopting pertinent technologies. The proposed model has been formulated based on a synthesis of design insights garnered from ten experts, obtained through focus group interviews. Leveraging these initial insights, we delineate potential applications of GenAI in AR.

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Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. An Exploratory Study on Multi-modal Generative AI in AR Storytelling

    cs.HC 2025-05 conditional novelty 6.0 of 10

    The paper maps how storytellers prefer to use AI-generated text, audio, images, videos, and 3D content to augment AR stories, based on a 223-video analysis and two user studies with 30 participants.

  2. CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence

    cs.HC 2025-01 conditional novelty 6.0 of 10

    CARING-AI combines ChatGPT text generation, environment scanning, and smoothed text-to-motion diffusion to let authors create spatially grounded AR avatar instructions without coding or motion capture.

  3. Vision-Based Multimodal Interfaces: A Survey and Taxonomy for Enhanced Context-Aware System Design

    cs.HC 2025-01 conditional novelty 4.0 of 10

    A systematic survey and taxonomy of vision-based multimodal interfaces, organized around a Macro-Micro-Macro framework for context-aware system design.

  4. Exploring Device-Oriented Video Encryption for Hierarchical Privacy Protection in AR Content Sharing

    cs.HC 2024-11 reject novelty 4.0 of 10

    The paper sketches a device-oriented hierarchical ROI encryption scheme for AR sharing, but it is a preliminary position piece without new measurements.

  5. MS2Mesh-XR: Multi-modal Sketch-to-Mesh Generation in XR Environments

    cs.CV 2024-12 conditional novelty 3.0 of 10

    A system that turns mid-air sketches plus voice into textured 3D meshes in XR by chaining ControlNet image generation with convolutional mesh reconstruction.

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