Smartphone-assisted smooth live video broadcast on wearable cameras

Jiwei Li, Zhe Peng, Bin Xiao
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引用次数: 5

Abstract

Wearable cameras require connecting to cellular-capable devices (e.g., smartphones) so as to provide live broadcast services for worldwide users when Wi-Fi is unavailable. However, the constantly changing cellular network conditions may substantially slow down the upload of recorded videos. In this paper, we consider the scenario where wearable cameras upload live videos to remote distribution servers under cellular networks, aiming at maximizing the quality of uploaded videos while meeting the delay requirements. To attain the goal, we propose a dynamic video coding approach that utilizes dynamic video recording resolution adjustment on wearable cameras and Lyapunov based video preprocessing on smartphones. Our proposed resolution adjustment algorithm adapts to network condition changes, and reduces the overheads of video preprocessing. Due to the property of Lyapunov optimization framework, our proposed video preprocessing algorithm delivers near-optimal video quality while meeting the upload delay requirements. Our evaluation results show that our approach achieves up to 50% reduction in power consumption on smartphones and up to 60% reduction in average delay, at the cost of slightly compromised video quality.
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智能手机辅助可穿戴摄像头流畅的视频直播
可穿戴相机需要连接到具有蜂窝功能的设备(例如智能手机),以便在Wi-Fi不可用时为全球用户提供直播服务。然而,不断变化的蜂窝网络条件可能会大大减慢录制视频的上传速度。在本文中,我们考虑在蜂窝网络下,可穿戴摄像机将实时视频上传到远程分发服务器的场景,以最大限度地提高上传视频的质量,同时满足延迟要求。为了实现这一目标,我们提出了一种动态视频编码方法,该方法利用可穿戴相机上的动态视频录制分辨率调整和智能手机上基于Lyapunov的视频预处理。我们提出的分辨率调整算法能够适应网络条件的变化,降低了视频预处理的开销。由于Lyapunov优化框架的特性,我们提出的视频预处理算法在满足上传延迟要求的同时提供了接近最优的视频质量。我们的评估结果表明,我们的方法可以将智能手机的功耗降低50%,平均延迟降低60%,但代价是视频质量略有下降。
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