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An Attention-Information-Based Spatial Adaptation Framework for Browsing Videos via Mobile Devices

机译:基于注意力信息的空间适应框架,用于通过移动设备浏览视频

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With the growing popularity of personal digital assistant devices and smart phones, more and more consumers are becoming quite enthusiastic to appreciate videos via mobile devices. However, limited display size of the mobile devices has been imposing significant barriers for users to enjoy browsing high-resolution videos. In this paper, we present an attention-information-based spatial adaptation framework to address this problem. The whole framework includes two major parts: video content generation and video adaptation system. During video compression, the attention information in video sequences will be detected using an attention model and embedded into bitstreams with proposed supplement-enhanced information (SEI) structure. Furthermore, we also develop an innovative scheme to adaptively adjust quantization parameters in order to simultaneously improve the quality of overall encoding and the quality of transcoding the attention areas. When the high-resolution bitstream is transmitted to mobile users, a fast transcoding algorithm we developed earlier will be applied to generate a new bitstream for attention areas in frames. The new low-resolution bitstream containing mostly attention information, instead of the high-resolution one, will be sent to users for display on the mobile devices. Experimental results show that the proposed spatial adaptation scheme is able to improve both subjective and objective video qualities.
机译:随着个人数字助理设备和智能电话的日益普及,越来越多的消费者变得非常热衷于通过移动设备欣赏视频。然而,移动设备的有限的显示尺寸已经为用户享受浏览高分辨率视频带来了很大的障碍。在本文中,我们提出了一种基于注意力信息的空间适应框架来解决这一问题。整个框架包括两个主要部分:视频内容生成和视频适配系统。在视频压缩期间,将使用注意力模型检测视频序列中的注意力信息,并将其嵌入具有建议的补充增强信息(SEI)结构的比特流中。此外,我们还开发了一种创新方案来自适应地调整量化参数,以同时提高整体编码的质量和对关注区域进行转码的质量。当高分辨率比特流传输到移动用户时,我们早先开发的快速转码算法将应用于为帧中的关注区域生成新的比特流。新的低分辨率比特流将主要包含注意力信息,而不是高分辨率的比特流,将发送给用户以显示在移动设备上。实验结果表明,提出的空间自适应方案能够同时改善主观和客观视频质量。

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