Fast video coding: estimation-based control of video codec complexity

快速视频编码：基于估计的视频编解码器复杂度控制

• 批准号: EP/E027024/1
• 负责人: Yafan Zhao
• 金额: $ 37.62万
• 依托单位: Robert Gordon University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FE027024%2F1
• 关键词: Fast; video; coding; estimation; based

We seek funding to address the problem of video compression on devices with limited processing resources. This is an issue for mobile platforms, where battery power and processing capabilities are limited, and for systems in which a video codec competes with other applications for processor resources. With the adoption of complex video coding standards (such as H.264/AVC) for consumer and mobile applications, the problem of computationally-efficient video coding is becoming increasingly important. It is vital to research and develop high quality video compression with controlled, low processor utilisation. This will make it possible to extend the battery life of mobile video devices (because a lower-power processor consumes less battery power) and to accommodate more software applications on a single processor.To date, the typical approach to the problem of limited processing resources is to reduce video frame rate and/or reduce compression quality in order to meet a computational constraint, leading to poor quality, jerky video images and unpredictable performance. This is unpleasant for the general consumer and unacceptable for specialist application such as remote surveillance and remote medical diagnosis. In contrast, our solution offers a way of managing video coding complexity, maintaining smooth video with good image quality.This proposal has two unique aspects. The first aspect is a novel method of reducing the complexity of video coding. The problem of evaluating and choosing coding modes is analysed and placed in a Bayesian framework. An adaptive algorithm maintains excellent video quality whilst offering a controllable reduction in computation, out-performing existing heuristic approaches. The second aspect is a system for controlling and managing coding complexity based on real-time measurements and targets. This enables a codec to maintain smooth, clear video images and to adapt to changes in scene content and available processing capability. We will develop and integrate these two concepts into a system that offers, for the first time, control of video codec complexity in an adaptive, analytic framework. The outcomes of this work will be of direct benefit to developers and integrators of next generation video-based platforms.The project will be led by Dr Iain Richardson, internationally recognised for his work on standards-based video coding. Dr Richardson and Dr Zhao (co-investigator) are experts in the field of video codec complexity management. Visiting researcher Professor Maja Bystrom of Boston University has already collaborated with the research team in developing the research tools that will form the basis of this project. BT Research (Multimedia Coding Analysis Group) will provide expert advice from an industry perspective.

我们寻求资金来解决具有有限处理资源的设备上的视频压缩问题。这是移动平台，电池电量和处理功能受到限制的问题，以及视频编解码器与其他应用程序竞争处理器资源的系统。随着用于消费者和移动应用程序的复杂视频编码标准（例如H.264/AVC），计算高效的视频编码问题变得越来越重要。通过受控的，低处理器的利用来研究和开发高质量的视频压缩至关重要。这将使可以延长移动视频设备的电池寿命（因为较低的处理器消耗了较小的电池电量）并在单个处理器上容纳更多的软件应用程序。到目前为止，解决有限处理资源问题的典型方法是降低视频帧速率和/或降低压缩质量，以达到计算限制，以达到差异质量，质量不佳，JERKY质量，JIRY质量，无预定的效果。对于一般消费者来说，这是不愉快的，对于远程监视和远程医学诊断等专业应用，这是不可接受的。相比之下，我们的解决方案提供了一种管理视频编码复杂性，以良好的图像质量保持流畅的视频的方法。该提案具有两个独特的方面。第一个方面是一种新颖的方法，可降低视频编码的复杂性。评估和选择编码模式的问题被分析并放置在贝叶斯框架中。一种自适应算法可保持出色的视频质量，同时提供可控的计算减少，超过现有的启发式方法。第二个方面是基于实时测量和目标控制和管理编码复杂性的系统。这使编解码器能够保持光滑，清晰的视频图像，并适应场景内容和可用处理能力的变化。我们将开发并将这两个概念整合到一个系统中，该系统首次提供了自适应，分析框架中视频编解码器复杂性的控制。这项工作的结果将对基于下一代视频的平台的开发人员和集成商有直接的好处。该项目将由Iain Richardson博士领导，Iain Richardson博士因其在基于标准的视频编码方面而受到国际认可。 Richardson博士和Zhao博士（共同投资者）是视频编解码复杂性管理领域的专家。波士顿大学的访问研究员Maja Bystrom教授已经与研究团队合作开发了将构成该项目基础的研究工具。 BT研究（多媒体编码分析小组）将从行业的角度提供专家建议。