以运动强度感知增强无人机视频传输

R. Immich, E. Cerqueira, M. Curado
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引用次数: 11

摘要

最近,随着军用和民用应用的数量增加,配备视频的无人机(UAV)的使用也在增加。这表明需要一种自适应视频感知机制,能够克服与稀缺网络资源、设备移动以及高错误率相关的许多挑战,以确保良好的视频质量传输。前向纠错(FEC)技术可以量身定制,在易出错和高移动性的网络中提供具有体验质量(QoE)保证的自适应保护。此外,每个视频序列的独特特征,如空间复杂性和时间强度,强烈地影响了丢包对QoE的影响。本文提出了一种基于模糊逻辑的自适应运动强度和视频感知FEC机制,以保障无人机实时视频传输不丢包,在节省资源的同时提供更好的用户体验。通过实验证明了该机制与相关工作相比的优点和缺点,并使用QoE指标进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards the enhancement of UAV video transmission with motion intensity awareness
The use of video-equipped Unmanned Aerial Vehicles (UAV) has been increasing recently, along with the number of available applications for military and civilian employment. This unveils the need for an adaptive video-aware mechanism capable of overcoming a number of challenges related to the scarce network resources, device movement, as well as high error rates, to ensure a good video quality delivery. Forward Error Correction (FEC) techniques can be tailored to provide adaptive protection with Quality of Experience (QoE) assurance over error-prone and high-mobility networks. Besides that, unique characteristics of each video sequence, such as the spatial complexity and the temporal intensity, strongly affect how the QoE will be impacted by the packet loss. This paper proposes an adaptive motion intensity and video-aware FEC mechanism with the aid of Fuzzy logic to safeguard UAV real-time video transmissions against packet loss, providing a better user experience, while saving resources. The advantages and drawbacks of the proposed mechanism in comparison to the related work are evidenced through experiments and assessed by using QoE metrics.
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