The case for context-aware compression

Xuan Bao, Trevor Narayan, A. A. Sani, Wolfgang Richter, Romit Roy Choudhury, Lin Zhong, M. Satyanarayanan
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引用次数: 6

Abstract

The proliferation of pictures and videos in the Internet is imposing heavy demands on mobile data networks. This demand is expected to grow rapidly and a one-fit-all solution is unforeseeable. While researchers are approaching the problem from different directions, we identify a human-centric opportunity to reduce content size. Our intuition is that humans exhibit unequal interest towards different parts of a content, and parts that are less important may be traded off for price/performance benefits. For instance, a picture with the Statue of Liberty against a blue sky may be partitioned into two categories -- the semantically important statue, and the less important blue sky. When the need to minimize bandwidth/energy is acute, only the picture of the statue may be downloaded, along with a meta tag "background: blue sky". Once downloaded, an arbitrary "blue sky" may be suitably inserted behind the statue, reconstructing an approximation of the original picture. As long as the essence of the picture is retained from the human's perspective, such an approximation may be acceptable. This paper attempts to explore the scope and usefulness of this idea, and develop a broader research theme that we call context-aware compression.
上下文感知压缩的案例
互联网上图片和视频的激增给移动数据网络带来了巨大的需求。预计这一需求将迅速增长,而一刀切的解决方案是不可预见的。虽然研究人员正在从不同的方向研究这个问题,但我们发现了一个以人为中心的机会来减少内容大小。我们的直觉是,人类对内容的不同部分表现出不平等的兴趣,而不太重要的部分可能会被价格/性能利益所交换。例如,自由女神像与蓝天的映衬可以分为两类——语义上重要的雕像和不那么重要的蓝天。当需要最大限度地减少带宽/能量时,只能下载雕像的图片,以及“背景:蓝天”的元标签。一旦下载,一个任意的“蓝天”可能会适当地插入雕像后面,重建一个近似的原始图片。只要从人的角度保留图片的本质,这样的近似是可以接受的。本文试图探索这个想法的范围和有用性,并开发一个更广泛的研究主题,我们称之为上下文感知压缩。
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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