During collaboration in XR (eXtended Reality), users typically share and interact with virtual objects in a common, shared virtual environment. Specifically, collaboration among users in Mixed Reality (MR) requires knowing their position, movement, and understanding of the visual scene surrounding their physical environments. Otherwise, one user could move an important virtual object to a position blocked by the physical environment for others. However, even for a single physical environment, 3D reconstruction takes a long time and the produced 3D data is typically very large in size. Also, these large amounts of 3D data take a long time to be streamed to receivers making real-time updates on the rendered scene challenging. Furthermore, many collaboration systems in MR require multiple devices, which take up space and make setup difficult. To address these challenges, in this paper, we describe a single-device system called Collaborative Adaptive Mixed Reality Environment (CAMRE). We build CAMRE using the scene understanding capabilities of HoloLens 2 devices to create shared MR virtual environments for each connected user and demonstrate using a Leader-Follower(s) paradigm: faster reconstruction and scene update times due to smaller data. Consequently, multiple users can receive shared, synchronized, and close-to-real-time latency virtual scenes from a chosen Leader, based on their physical position and movement. We also illustrate other expanded features of CAMRE MR virtual environment such as navigation using a real-time virtual mini-map and X-ray vision for handling adaptive wall opacity. We share several experimental results that evaluate the performance of CAMRE in terms of the network latency in sharing virtual objects and other capabilities.

翻译：在扩展现实（XR）协作过程中，用户通常在共享的虚拟环境中交互虚拟对象。具体而言，混合现实（MR）中的用户协作需要知晓彼此的位置、运动轨迹以及对周围物理环境视觉场景的理解。否则，某用户可能将重要虚拟对象移动至被他人物理环境遮挡的位置。然而，即便针对单一物理环境，三维重建仍需较长时间，且生成的三维数据量通常十分庞大。此外，这些海量三维数据在流式传输至接收端时耗时较长，导致渲染场景的实时更新面临挑战。同时，现有MR协作系统多需多台设备，既占用空间又增加部署难度。为解决上述问题，本文提出一种名为"协作自适应混合现实环境"（CAMRE）的单设备系统。我们利用HoloLens 2设备的场景理解能力构建CAMRE，为每位连接用户创建共享的MR虚拟环境，并采用领导者-跟随者（Leader-Follower(s)）范式验证其性能：因数据量更小，实现了更快的场景重建与更新速度。基于此，多位用户可根据自身物理位置与运动轨迹，从选定领导者处接收共享、同步且接近实时延迟的虚拟场景。我们还展示了CAMRE MR虚拟环境的扩展功能，如基于实时虚拟小地图的导航及自适应墙壁不透明处理的X射线视觉技术。最后，通过多项实验评估CAMRE在虚拟对象共享时的网络延迟等性能指标。