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

Area of Science:

• Human-Computer Interaction
• Virtual Reality
• Collaborative Systems

Background:

• Mixed Reality (MR) telecollaboration enables remote users to share virtual objects for collaborative tasks.
• Current MR visualization methods struggle to balance spatiality, fidelity, and real-time performance across different task contexts.
• Existing systems often use fixed modality combinations and lack adaptive switching, disrupting user workflow.

Purpose of the Study:

• To propose and evaluate an adaptive object visualization system for Mixed Reality telecollaboration.
• To investigate how task type and viewing distance influence user prioritization of visualization aspects (spatiality, fidelity, real-time performance).
• To develop temporal switching schemes for modality transitions when preferred visualizations are unavailable.

Main Methods:

• Coupling task type with user viewing distance to define spatio-temporal contexts.
• Examining user-prioritized visualization aspects and modality switching thresholds within these contexts.
• Developing and implementing an automatic visualization adaptation system (CollabVisAdapt) with temporal switching schemes.

Main Results:

• Demonstrated that spatio-temporal context significantly impacts user preferences for visualization aspects in MR telecollaboration.
• Validated the effectiveness of automatic adaptation in optimizing visualization for different task phases.
• User study confirmed the usability and effectiveness of the CollabVisAdapt system in a remote maintenance scenario.

Conclusions:

• Adaptive object visualization based on spatio-temporal contexts significantly enhances MR telecollaboration.
• The CollabVisAdapt system provides a practical solution for dynamic modality switching, improving user experience.
• This approach optimizes the balance between spatiality, fidelity, and real-time performance in shared MR environments.