Augmented Object Intelligence with XR-Objects
<|reference_start|>Augmented Object Intelligence with XR-Objects: Seamless integration of physical objects as interactive digital entities remains a challenge for spatial computing. This paper explores Artificial Object Intelligence (AOI) in the context of XR, an interaction paradigm that aims to blur the lines between digital and physical by equipping real-world objects with the ability to interact as if they were digital, where every object has the potential to serve as a portal to digital functionalities. Our approach utilizes real-time object segmentation and classification, combined with the power of Multimodal Large Language Models (MLLMs), to facilitate these interactions without the need for object pre-registration. We implement the AOI concept in the form of XR-Objects, an open-source prototype system that provides a platform for users to engage with their physical environment in contextually relevant ways using object-based context menus. This system enables analog objects to not only convey information but also to initiate digital actions, such as querying for details or executing tasks. Our contributions are threefold: (1) we define the AOI concept and detail its advantages over traditional AI assistants, (2) detail the XR-Objects system's open-source design and implementation, and (3) show its versatility through various use cases and a user study.<|reference_end|>
@article{dogan2024augmented,
    title={Augmented Object Intelligence with XR-Objects},
    author={Mustafa Doga Dogan, and Eric J. Gonzalez, and Karan Ahuja, and Ruofei
  Du, and Andrea Colac{c}o, and Johnny Lee, and Mar Gonzalez-Franco, and David
  Kim},
    journal={arXiv preprint arXiv:2404.13274},
    year={2024},
    doi={10.1145/3654777.3676379},
    archivePrefix={arXiv},
    eprint={2404.13274},
    primaryClass={cs.HC cs.AI}
}