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Experimental Study of Video Fusion for Multi-View Video Streaming in Mobile Media Cloud

机译:移动媒体云中多视点视频流视频融合的实验研究

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Nowadays, mobile users are not just content with a quick access to Internet when they are watching various types of videos, but also expecting a better video viewing experience. The reality is that decoding videos will consume very large resources of mobile devices. However, the resources of mobile devices are limited in terms of CPU, the main memory and so on, which impedes the performance enhancement. Fortunately, the emergence of mobile media cloud makes it possible to lighten decoding load on mobile devices. Cloud computing has an outstanding performance in rendering diverse services, strong computation ability, and great storage capacity in a relatively lower cost, which provides an effective channel out for the present dilemma. In this paper, we focus on the experimental study of video fusion method for multi-view video streaming under mobile media cloud environment. Firstly, we conduct a large quantity of collection experiments and find that decoding load of videos follows the power function model, which demonstrates that video fusion of multi-view videos at cloud side may effectively reduce the CPU usage of decoding at mobile side. Secondly, we further quantify the condition when the video fusion method can reduce the CPU usage of mobile devices along with its corresponding reduction rates.
机译:如今,移动用户不仅在观看各种类型的视频时对快速访问Internet感到满意,而且还希望获得更好的视频观看体验。现实情况是,对视频进行解码将消耗很大数量的移动设备资源。然而,移动设备的资源在CPU,主存储器等方面受到限制,这阻碍了性能的提高。幸运的是,移动媒体云的出现使减轻移动设备上的解码负载成为可能。云计算在以较低的成本提供多种服务方面具有出色的性能,强大的计算能力和巨大的存储容量,这为当前的困境提供了有效的解决方案。在本文中,我们专注于在移动媒体云环境下用于多视图视频流的视频融合方法的实验研究。首先,我们进行了大量的收集实验,发现视频的解码负载遵循幂函数模型,这表明云端多视点视频的视频融合可以有效降低移动端解码的CPU使用率。其次,我们进一步量化了视频融合方法可以降低移动设备的CPU使用率及其相应降低率的条件。

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