研究了不利网络条件下兴趣区编码对FPV无人机飞行QoE的影响

Lovro Boban, Lorenzo Catania, D. Allegra, M. Sužnjević
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引用次数: 0

摘要

在本文中,我们评估了一种提高无人机飞行员体验质量的方法。我们研究了无人机通过基于IP的网络(如5G)以第一人称视角控制的用例。在拥塞情况下,无人机发送的视频需要以较低的比特率进行编码,以避免严重的视频伪影和体验质量下降。我们评估了如何在低带宽的退化网络条件下最大化无人机飞行员的体验质量的方法。我们评估了兴趣区域编码和灰度编码对视频质量主观指标的影响。测试是通过无人机驾驶模拟器和商用第一人称视角谷歌进行的。我们的研究结果,基于样本量(n = 24),表明投资回报率和灰度编码,在几乎所有情况下,要么没有影响,要么对无人机飞行员的感知视频质量产生负面影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating the effect of Region of Interest coding on the QoE of FPV drone piloting under adverse network conditions
In this paper we evaluate an approach for increasing Quality of Experience for drone pilots. We look at the use case in which the drone is controlled in first-person view over an IP based network such as 5G. In case of congestion, the video sent by the drone needs to be encoded at a lower bitrate so as to avoid severe video artefacts and Quality of Experience degradation. We evaluate methods of how to maximize Quality of Experience for the drone pilots in degraded network conditions with low bandwidth. We evaluate the impact of Region of Interest coding and greyscale coding on subjective metrics of video quality. The testing is performed through a drone driving simulator and using commercial first-person view googles. Our findings, based on a sample size of (n = 24), indicate that ROI and greyscale coding have, in almost all cases, either no impact or a negative impact on perceived video quality of a drone pilot.
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