CollabVisAdapt: Spatio-Temporal Context-Aware Adaptation of Shared Object Visualization for MR Telecollaboration

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Abstract
Mixed Reality (MR) telecollaboration aims to enable users to share local objects as real-time synchronized virtual replicas to remote partners and collaborate on physical tasks as if they were co-located. However, in everyday scenarios with mobile and easy-to-setup MR devices, visualizing shared objects in a single modality, ranging from 2D images to 3D reconstruction, struggles to simultaneously optimize all the aspects of Spatiality, Fidelity, and Real-time performance. To overcome this issue, existing methods explore integrating multiple visualization modalities to leverage their respective advantages in subsets of the three aspects. However, they focus on fixed modality combinations without considering user-centered task contexts and workflow, where users may prioritize different aspects of the visualization across task phases. Moreover, they lack support for switching or require manual switching across modalities, which could become disruptive and tiring. In this paper, we propose adapting object visualization based on spatio-temporal contexts in telecollaboration. Specifically, we first couple task type with the user's relative viewing distance as the spatial context, and examine its impact on users' prioritized visualization aspects, and the corresponding switching thresholds. With differing generation speeds of modalities, we then explore temporal switching schemes when the preferred modality is not immediately available. With the obtained design choices, we implement CollabVisAdapt, a proof-of-concept prototype that supports automatic adaptation of object visualization based on spatio-temporal contexts in MR telecollaboration. A user study in remote maintenance verifies the effectiveness of the proposed workflow with adaptive visualization and the usability of the system.
Funding Information
  • National Natural Science Foundation of China (62502375)
  • National Natural Science Foundation of China (62192781)
  • National Natural Science Foundation of China (62172326)
  • National Natural Science Foundation of China (62137002)
  • National Natural Science Foundation of China (62302384)
  • Key Research and Development Project in Shaanxi Province (2022GXLH-01-03)
  • Project of China Knowledge Centre for Engineering Science and Technology

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