Augmented Object Intelligence with XR-Objects

TL;DR

This paper introduces XR-Objects, a system that enhances physical objects with digital interaction capabilities using real-time segmentation, classification, and multimodal language models, enabling seamless physical-digital integration in XR environments.

Contribution

It defines the Augmented Object Intelligence concept, presents an open-source XR-Objects system, and demonstrates its versatility through use cases and a user study.

Findings

Effective real-time object interaction without pre-registration

Versatile use cases demonstrating digital-physical integration

Positive user feedback on system usability

Abstract

Seamless integration of physical objects as interactive digital entities remains a challenge for spatial computing. This paper explores Augmented 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.