Content-aware energy prediction for video streaming in mobile devices

Yi-Chan Li, Hisu-Hsien Li, Han-Lin Li, Chia-Lin Yang
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Abstract

As personal multimedia devices become mainstream consumer products, an energy-aware on-demand video streaming system for portable devices is critical. A critical component of an energy-aware video streaming system is an accurate energy prediction scheme for video decoding. In this paper, we propose the first content-aware energy predictor for video playback. We correlate video attributes with decoding energy through linear regression. The average prediction error achieved by proposed content-aware energy prediction scheme is only 1.88%.
移动设备中视频流的内容感知能量预测
随着个人多媒体设备成为主流消费产品,便携式设备的节能点播视频流系统至关重要。能量感知视频流系统的关键组成部分是准确的视频解码能量预测方案。在本文中,我们提出了第一个用于视频播放的内容感知能量预测器。我们通过线性回归将视频属性与解码能量关联起来。所提出的内容感知能量预测方案的平均预测误差仅为1.88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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