AI-based Image-As-Video Streaming
AI-based Image-As-Video Streaming
批准号:
59404
负责人:
金额:
$6.37万
依托单位:
依托单位国家:
英国
项目类别:
Feasibility Studies
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --
中文摘要
Deep Render Ltd是一家总部位于伦敦的高科技初创公司,开发下一代基于人工智能的媒体压缩算法。我们的专有和专利技术处于机器学习研究的前沿。深度渲染结合了人工智能、统计学和信息论的领域,以解开图像和视频压缩的基本限制:人眼是人类已知的最好的数据压缩器,其压缩比至少比迄今为止开发的任何东西好2000倍。我们的生物压缩方法通过非线性、基于学习的方法近似人眼的神经过程,从而创造了一类新型的高效压缩算法。我们是这一领域的世界领导者,我们独特的基于人工智能的图像压缩技术已经比以前最好的压缩标准提供了75%的效率提升。随着全球数据消耗呈指数级增长,超过80%的流量是图像/视频,Deep Render基于人工智能的压缩技术对于绕过宽带限制至关重要。COVID-19的爆发现在加速了这一增长,由于危机,互联网使用量大幅增加。特别是对直播和视频聊天服务的需求。因此,我们希望将我们已经工作的图像压缩编解码器应用于实时视频流。该项目的结果是将我们的图像压缩编解码器扩展到图像即视频直播流媒体编解码器,比当前最先进的编解码器效率至少提高75%。我们的目标客户是实时视频聊天服务(Zoom, Skype, Microsoft Teams),以及娱乐行业,包括直播流媒体平台(Twitch, Facebook, Instagram, YouTube)。我们的价值主张很容易理解。通过将文件大小缩小75%,我们直接将互联网直播的带宽供应增加了4倍。通过减小文件大小来增加带宽供应,比通过使用越来越多的光纤电缆重新布线来增加带宽供应更具价值和时间效率。深度渲染将帮助创造一个新的时代,在这个时代,带宽限制是一个过去的问题。由于COVID - 19解决这个问题变得更加重要,Deep Render决心创建一个快速的解决方案。
英文摘要
Deep Render Ltd is a London based deep-tech start-up developing the next generation of AI-based media compression algorithms. Our proprietary and patented technology is at the forefront of machine learning research.Deep Render is combining the fields of artificial intelligence, statistics and information theory to unlock the fundamental limits of image and video compression: The human eye is the best data compressor known to humanity - with compression ratios at least 2,000 times better than everything developed to date. Our Biological Compression approach approximates the neurological processes of the human eye through a non-linear, learning-based approach, thereby creating a novel class of highly efficient compression algorithms. We are world leaders in this domain, and our unique, AI-based image compression technology is already providing a 75% efficiency gain over the best previous compression standards.As global data consumption is growing exponentially with more than 80% of traffic being Image/Video, Deep Render's AI-based compression technology is vital to bypass broadband constraints. The outbreak of COVID-19 has now accelerated this growth, as a result of the crisis, internet usage has increased significantly. In particular, the demand for live-streaming and video-chat services. Therefore we want to apply our already working image compression codec to live-video streaming.The outcome of the project is to extend our image compression codec to an image-as-video live-streaming codec, at least 75% more efficient than the current state-of-the-art. Our target customers are the live video chat services (Zoom, Skype, Microsoft Teams), as well as the entertainment industry, including live streaming platforms (Twitch, Facebook, Instagram, YouTube).Our value proposition is easy to understand. By making file sizes 75% smaller, we directly increase the bandwidth supply of the internet for live-streaming by a factor of 4\. Increasing the bandwidth supply by making file sizes smaller, is magnitudes more value- and time-efficient than increasing the bandwidth supply through rewiring the globe with progressively more fibre-cables. Deep Render is going to help create a new age in which bandwidth constraints are a problem of the past. As a result of COVID 19 solving this problem has gained more importance and Deep Render is determined to create a fast solution.
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