CIF: Small: Multiterminal Video Coding: From Theory to Practice

CIF：小型：多终端视频编码：从理论到实践

• 批准号: 1216001
• 负责人: Zixiang Xiong
• 金额: $ 14.96万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1216001&HistoricalAwards=false
• 关键词: CIF; Small; Multiterminal; Video; Coding

Multiterminal (MT) video coding considers the problem of separate compression and joint decompression of multiple correlated video sources. Driven by a host of emerging applications (e.g., in network communications, distributed video sensor networks and camera arrays, and distributed inference), MT video coding has become a very active area of research in the past ten years.This research addresses both the theory of MT source coding and practice of MT video coding, with the aim of using the theory to guide practice. It involves: 1) identifying new classes of problems of quadratic Gaussian MT source coding with tight sum-rate bound or giving sufficient conditions for sum-rate tightness; 2) taking an approximation approach when sum-rate tightness cannot be proved; 3) performing MT source code constructions based on Slepian-Wolf coded quantization for random coding and hybrid random-structured coding; and 4) spearheading the practical application of MT video coding for camera arrays and distributed video sensor networks, with focus on depth camera assisted MT video coding.

多终端（MT）视频编码考虑多个相关视频源的单独压缩和联合解压缩的问题。在许多新兴应用（例如网络通信、分布式视频传感器网络和摄像机阵列以及分布式推理）的推动下，机器翻译视频编码在过去十年中已成为一个非常活跃的研究领域。这项研究既涉及理论又涉及MT源码编码和MT视频编码实践，旨在用理论指导实践。它涉及： 1) 识别具有严格和率界限的二次高斯 MT 源编码的新问题类别，或为和率严格性提供充分条件； 2）当无法证明和率紧性时，采用近似方法； 3) 执行基于Slepian-Wolf编码量化的MT源代码构造，用于随机编码和混合随机结构编码； 4) 引领相机阵列和分布式视频传感器网络的MT视频编码的实际应用，重点是深度相机辅助的MT视频编码。