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.
Context-Aware Mixed Reality: A Framework for Ubiquitous Interaction
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abstract
Mixed Reality (MR) is a powerful interactive technology that yields new types of user experience. We present a semantic based interactive MR framework that exceeds the current geometry level approaches, a step change in generating high-level context-aware interactions. Our key insight is to build semantic understanding in MR that not only can greatly enhance user experience through object-specific behaviours, but also pave the way for solving complex interaction design challenges. The framework generates semantic properties of the real world environment through dense scene reconstruction and deep image understanding. We demonstrate our approach with a material-aware prototype system for generating context-aware physical interactions between the real and the virtual objects. Quantitative and qualitative evaluations are carried out and the results show that the framework delivers accurate and fast semantic information in interactive MR environment, providing effective semantic level interactions.
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CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence
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.