复杂广域场景中无重叠摄像机间行人关联与语义分析研究

项目名称： 复杂广域场景中无重叠摄像机间行人关联与语义分析研究

项目编号： No.61202157

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 计算机科学学科

项目作者： 连国云

作者单位： 深圳大学

项目金额： 23万元

中文摘要： 视频监控系统已被广泛使用，但如何利用计算机技术实现对重点目标在广域监控场景中主动、持续的跟踪，是目前急需解决的问题。而摄像机间的目标关联又是解决这个问题的前提和基础。无重叠摄像机间行人关联是广域视频监控领域中一个极具挑战性的研究方向。针对目前该研究方向在复杂场景中存在的若干关键问题，本项目着重研究三个方面的内容：1）基于概率图模型和图匹配理论的行人关联模型研究，并给出复杂场景下较优的无重叠摄像机间行人关联算法；2）摄像机间转移关系模型的自适应动态估计研究；3）低质量图像的高分辨率复原方法及适合实际视频监控的行人特征表达方法研究。在行人关联研究的基础上，利用行人的运动轨迹重构和产生式规则，探讨了行人在整个监控场景的语义分析研究。本项目的理论成果和算法将大大丰富广域视频监控领域的研究与发展，同时也将促进计算机视觉、模式识别、图像处理和机器学习等相关学科的发展。

中文关键词： 视频监控；行人关联；特征表达；概率图模型；

英文摘要： The video surveillance system has been widely used。 But how to use computer technology to achieve the active and continuous tracking of the key objects in the wide-area monitoring scene, is urgently needed to resolve. And the basic premise of solving this problem is to achieve the object correspondence across multiple cameras. Pedestrians correspondence across multiple non-overlapping camera views is a challenging problem in the wide-area video surveillance field. For the existing key issues of this current research in the complex scene, this project focuses on three aspects: 1) studying the pedestrian correspondence model based on the probabilistic graphical model and graph matching theory and proposing a good pedestrian correspondence algorithm across non-overlapping camera views in the complex scene; 2) studying the adaptive dynamic estimation of the transfer relation model between two cameras; 3) studying the high-resolution recovery algorithms of the low-quality image and the pedestrian's features representation which is adaptive for real video surveillance. Based on the pedestrian correspondence research, we investigate the semantic analysis of the entire surveillance scene using the trajectory reconstruction and generative rule. The theoretical achievements and algorithms of this project will greatly enr

英文关键词： video surveillance；pedestrian correspondence；feature representation；probabilistic graphical model；