Many modern-day XR devices (e.g. mobile headsets, phones, etc.) lack the computing resources required to render complex 3D scenes in real-time. Typically, to render a high-resolution scene on a lightweight XR device, ...
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ISBN:
(纸本)9798350328387
Many modern-day XR devices (e.g. mobile headsets, phones, etc.) lack the computing resources required to render complex 3D scenes in real-time. Typically, to render a high-resolution scene on a lightweight XR device, 3D designers arduously decimate and fine-tune the objects. As an alternative, remote rendering systems can utilize powerful nearby servers to stream rendering results to a client. While this is a promising solution, it can introduce a variety of latency and reliability issues, especially under variable network conditions. In this paper, we present a distributed rendering system that combines both remote rendering and on-device, "local" rendering to add robustness to network fluctuations and device workloads. To maximize user QoE, our approach dynamically swaps an object's rendering medium, adjusting for client workload, low frame rates, and several perceptual characteristics. To model these characteristics, we perform a study under simulated conditions to measure how users perceive latency and complexity differences between objects in a scene. Using the results of the study, we then provide an algorithm for choosing the optimal object rendering medium, based on rendering complexity as well as network and latency models, ensuring that a target frame rate will be met. Finally, we evaluate this algorithm on a prototype implementation that can provide cross-platform split rendering using web technologies.
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