基于压缩感知融合深度的三维视频编码关键技术的研究

项目名称： 基于压缩感知融合深度的三维视频编码关键技术的研究

项目编号： No.61271212

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 无线电电子学、电信技术

项目作者： 王国中

作者单位： 上海大学

项目金额： 76万元

中文摘要： 为了实现自由视点的立体视频系统，需要传输多个视点数据及其对应的深度信号，并在接收端进行虚拟视点的合成。面对数据量庞大、编码后视点合成质量不高以及实时性较差等问题，需要探索兼具采集简单、复杂度低、鲁棒性较好且利于视点合成的三维视频编解码方法。本课题在深入分析分布式压缩感知、分布式视频编码、多视点视频编码、虚拟视点绘制以及人眼视觉特性等理论的基础上,研究一种全新基于压缩感知融合深度的三维视频编码系统方法，探索低复杂度、鲁棒性较好融合深度的三维视频编解码理论。项目的研究内容包括：基于分布式压缩感知的深度编码模型研究、基于压缩感知融合深度的三维视频编码系统及优化、基于虚拟合成视点质量的视觉压缩感知分析模型。本项目旨在探索新的三维视频编码理论，解决目前自由式立体视频在采集、压缩和传输中存在的问题。预计本项目所获得的具有知识产权的研究成果，将有助于推进我国3DTV的发展。

中文关键词： 自由视点视频编码；深度图像；压缩感知理论；虚拟视点绘制；分布式压缩感知

英文摘要： In order to achieve the Free- Viewpoint Video system,multiple viewpoint video data and its corresponding depth map are the need of transmission,and the virtual viewpoint synthesis should be adopted at the end of system. Facing the large quantity of data, the high complexity of three-dimensional video encoding as well as the poor quality of virtual viewpoint synthesis after coding,a novel three-dimensional video coding system which have some characteristices of simple acquisition,low encoding complexity and good robustness must be designed. Analysising deeply the theories of distributed compressive sensing, distributed video coding, multi-view video coding, virtual view rendering, and human visual system, the aims of this study is that a novel compression system of 3D video with depth map should be construction which have low encoding complexity and good robustness.The studies of project include: Distributed compressive sensing based on depth map, A system of 3D video coding with depth map based on compressing sensing and optimization, Distributed video analysis. This project aims to explore the new 3D video coding technology, and solve the problems acquisition, compression and transmission in the application of free viewpoint system. The research results of intellectual property rights obtained in this projec

英文关键词： Free viewpoint video coding；depth map；compressed sensing；virtual viewpoint rendering；distributed compressed sensing