Real-Time High-Quality Visualization for Volumetric Contents Rendering: A Lyapunov Optimization Framework

Hankyul Baek;Rhoan Lee;Soyi Jung;Joongheon Kim;Soohyun Park
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Abstract

Real-time volumetric contents streaming on augmented reality (AR) devices should necessitate a balance between end-users' quality of experience (QoE) and the latency requirements. Lowering the quality of the volumetric contents to diminish the latency hinders the user's QoE. Otherwise, setting the quality of volumetric contents relatively high to improve the users' QoE increases the latency, which can be challenging to meet user satisfaction in AR services. Based on this trade-off observation, our proposed method maximizes time-average AR quality under latency requirements, inspired by Lyapunov optimization framework. In order to control the AR quality depending on latency requirements, we control the point cloud rendering ratio in the volumetric contents under the concept of Lyapunov optimization. Our extensive evaluation demonstrates that our proposed method achieves desired performance improvements, i.e., avoiding latency growing while ensuring the high quality of the volumetric contents streaming in AR services.
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体积内容绘制的实时高质量可视化:一个Lyapunov优化框架
增强现实(AR)设备上的实时体积内容流应该需要在最终用户的体验质量(QoE)和延迟要求之间取得平衡。降低体积内容的质量以减少延迟阻碍了用户的QoE。否则,将体积内容的质量设置得相对较高以提高用户的QoE会增加延迟,这对于满足AR服务中的用户满意度可能是一项挑战。基于这种权衡观察,受李雅普诺夫优化框架的启发,我们提出的方法在延迟要求下使时间平均AR质量最大化。为了根据延迟要求控制AR质量,我们在Lyapunov优化的概念下控制了体积内容中的点云渲染率。我们的广泛评估表明,我们提出的方法实现了所需的性能改进,即避免了延迟增长,同时确保了AR服务中体积内容流的高质量。
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