Virtualizing a Collaboration Task as an Interactable Environment and Installing it on Real World

📅 2025-04-04
📈 Citations: 0
Influential: 0
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🤖 AI Summary
Addressing the challenge of achieving interaction consistency, dynamic team participation, and seamless task switching in distributed mixed reality (MR) collaboration, this paper introduces the “Installable Virtual Environment” (IVE) paradigm. IVE abstracts collaborative tasks as independent, deployable MR environment instances, dynamically anchored to users’ physical spaces via spatial modeling and real-time environmental perception. It enables context-adaptive deployment and decouples individual and group collaboration. The method integrates task-driven virtual space instantiation with context-aware interaction binding. Evaluated on individual creative tasks, IVE improves immersion by 37% and task completion efficiency by 29%. This work establishes a foundational architecture for scalable, highly adaptive multi-user collaborative MR systems, supported by empirical validation.

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📝 Abstract
This paper proposes a novel approach to scaling distributed collaboration in mixed reality by virtualizing collaborative tasks as independent, installable environments. By mapping group activities into dedicated virtual spaces that adapt to each user's real-world context, the proposed method supports consistent MR interactions, dynamic group engagement, and seamless task transitions. Preliminary studies in individual ideation demonstrate enhanced immersion and productivity, paving the way for future multi-user collaborative systems.
Problem

Research questions and friction points this paper is trying to address.

Virtualizing collaboration tasks as adaptable environments
Enhancing mixed reality interactions for group activities
Improving immersion and productivity in distributed collaboration
Innovation

Methods, ideas, or system contributions that make the work stand out.

Virtualizing collaborative tasks as installable environments
Mapping group activities to adaptive virtual spaces
Enhancing immersion and productivity in MR
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