发表机构
Iran Univ. of Science and Technology; Univ. of Tehran; INRS（伊朗科技大学; 德黑兰大学; 国家研究 Institute）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出将全息通信中的重建与渲染分离为慢速和快速回路，利用主动推断控制器优化重建时机与计算分配，显著降低交互延迟。
AI 中文摘要
全息型通信在观看者移动超出显示器的角度观看区域时需要生成新的全息图，而图像到3D重建每个资产需要数十秒。我们将这些操作分离为一个重建持久网格的慢速回路和一个从存储网格渲染每个视点的快速回路。快速回路耗时0.117秒，与相机运动无关，而完整重建需要13.8-14.8秒。一个主动推断控制器根据学习到的用户状态转换决定何时开始重建，是执行完整更新还是区域更新，以及基于单目深度细节度量分配多少计算资源。区域更新保留编辑区域外的几何形状。在一个模拟的100事件会话中，分离回路将每事件的平均延迟从14.8秒降至4.4秒（3.4倍）；预测性重建进一步将其降至1.7-2.9秒，具体取决于用户常规强度。
英文摘要
Holographic-type communication requires a new hologram when the viewer moves beyond the display's angular viewing zone, whereas image-to-3D reconstruction takes tens of seconds per asset. We separate these operations into a slow loop that reconstructs a persistent mesh and a fast loop that renders each viewpoint from the stored mesh. The fast loop takes 0.117 s independently of camera motion, compared with 13.8-14.8 s for a full reconstruction. An active-inference controller determines when to begin reconstruction from learned user-state transitions, whether to perform a full or regional update, and how much computation to allocate based on a monocular-depth detail measure. Regional updates preserve geometry outside the edited area. In a modeled 100-event session, separating the loops reduces mean latency per event from 14.8 to 4.4 s (3.4-fold); predictive reconstruction reduces it further to 1.7-2.9 s, depending on user routine strength.
Comments4 pages, 4 figures, 1 table
