面向安防监控的双目立体视频关注度分析与编码技术研究

项目名称： 面向安防监控的双目立体视频关注度分析与编码技术研究

项目编号： No.61271256

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： 阮若林

作者单位： 湖北科技学院

项目金额： 70万元

中文摘要： 面对日益严峻的社会治安形势，传统单摄像机监控体系无法获取目标的深度信息，难以满足刑事视频侦查的需要。双目立体视频监控能捕捉场景的深度信息，帮助甄别关键嫌疑要点，引起了广泛关注。针对双目立体视频监控的海量数据对存储和传输的巨大压力，研究者将人眼视觉特性引入立体视频压缩编码，但忽略了视点间感知机理及监控场景特性，制约了编码效率的提升。为此，本申请研究面向安防监控的双目立体视频关注度模型与编码技术。首先，从立体视频的双目竞争感知机理出发，建立双目立体视频关注度模型，指导双目立体视频的感知码率分配；其次，将监控场景背景时域缓变特性引入到视点合成预测，提高视间预测效率；最后，分析双目感知机理以及关注度因素对掩蔽效应的影响，研究基于双目立体视频恰可感知失真阈值的残差滤波方法，提高双目立体监控视频编码效率。预期本研究在同等主观质量下，降低20%的编码码率，满足传统视频监控体系向立体监控升级换代的需求。

中文关键词： 立体视频编码；双目立体视频关注度；视间预测；恰可感知失真；视点合成预测

英文摘要： Under the serious social security problems, the traditional surveillance system composed of single camera cannot obtain the depth information of the target and meet the demand of criminal investigation and evidence collection. Whereas by capturing the scene depth information and helping screen the key suspect points, the binocular stereo video surveillance has aroused widespread interest. In order to solve the enormous pressure of the stereo video surveillance mass data storage and transmission,the human visual system is introduced into the stereo video compressing coding by researchers, but the perception mechanism of inter-view and the inherent characteristics of monitoring the scene are neglected, hence the coding efficiency is affected. Therefore, this application puts forward the surveillance-oriented binocular stereo video attention model and its application for video coding. Firstly, by analyzing the binocular competition perception mechanisam of stereo video, it builds up an attention model of binocular stereo video coding framework to guide its perception rate allaction. Secondly, the background temporal slowly varing featurs of the monitoring scene is introduced into the view synthesis prediction to improve the efficiency of inter-view prediction. Finally, it studies the residual filter method based on

英文关键词： stereo video coding；binocular stereo video　attention；inter-view prediction；just noticeable difference；view synthesis prediction