Semantic-aware adaptation scheme for soccer video over MPEG-DASH

Shenghong Hu, Lingfen Sun, Chunxia Xiao, Chao Gui
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引用次数: 6

Abstract

In recent years, quality of experience (QoE) has been investigated and proved to have both influential factors on user's visual quality and perceptual quality, while the perceptual quality means user's requirement on personalized content should be acquired in optimized quality. That's to say, those segments holding user interested content such as highlights need to be allocated more network resource in a resource-limited streaming scenario. However, all the existing HTTP-based adaptive methods only focus the content-agnostic bitrate adaptation according to limited network resources or energy resource, since they ignored user perceived semantics on some important segments, which suffered less quality on the important segments than on those ordinary ones, so as to hurt the overall QoE. In this paper, we have proposed a new semantic-aware adaptation scheme for MPEG-DASH services, which decides how to preserve bandwidth and buffering time depending on content descriptors for the perceived important content to users. Further, a semantic-aware probe and adaptation (SMA-PANDA) algorithm has been implemented in a DASH client to compare with conventional bitrate adaptions. Preliminary results show that SMA-PANDA achieves better QoE and flexibility on streaming user's interested content on MPEG-DASH platform, and it also aggressively helps user interested content compete more resource to deliver high quality presentation.
基于MPEG-DASH的足球视频语义感知自适应方案
近年来,对体验质量(QoE)的研究证明,体验质量对用户的视觉质量和感知质量都有影响,而感知质量是指用户对个性化内容的需求应该以优化的质量来获得。也就是说,在资源有限的流媒体场景中,那些包含用户感兴趣的内容(如亮点)的部分需要分配更多的网络资源。然而,现有的基于http的自适应方法都是根据有限的网络资源或能量资源,只关注与内容无关的比特率自适应,忽略了用户在一些重要段上感知到的语义,在重要段上的质量不如普通段,从而影响了整体的质量质量。本文提出了一种新的语义感知的MPEG-DASH服务自适应方案,该方案根据用户感知到的重要内容的内容描述符来决定如何保留带宽和缓冲时间。此外,在DASH客户端中实现了语义感知探测和自适应(SMA-PANDA)算法,以与传统的比特率自适应进行比较。初步结果表明,SMA-PANDA在MPEG-DASH平台上对流媒体用户感兴趣的内容实现了更好的QoE和灵活性,并积极帮助用户感兴趣的内容竞争更多的资源来提供高质量的呈现。
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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