基于多源视频的大范围场景目标跟踪

项目名称： 基于多源视频的大范围场景目标跟踪

项目编号： No.61503381

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 其他

项目作者： 蔡莹皓

作者单位： 中国科学院自动化研究所

项目金额： 19万元

中文摘要： 随着对安全要求的日益迫切，结合传统监控视频和用户自生产视频对感兴趣目标进行监控已是必然趋势，对解决公共安全问题具有极大的应用价值。本项目提出基于多源视频（监控视频和众包视频）的大范围场景目标跟踪。目前，大范围场景目标跟踪系统大多基于多个固定监控摄像机，难以扩展到多源视频下的目标跟踪。本项目拟对多源视频下大范围场景目标跟踪进行系统的研究，提出多源视频数据统一的表示形式，通过基于地理空间信息的图像搜索方法快速搜索并返回和目标跟踪应用最为相关的视频，提高多摄像机监控系统的可扩展性和时间效率；将视频的时空上下文信息嵌入到跨视频目标匹配中，提高目标跟踪在大范围真实场景中的性能。本项目为大数据视频监控时代提供一种有效的解决方案，具有重要的科学研究意义和广泛的应用前景。

中文关键词： 计算机视觉；目标跟踪；移动视频；多摄像机；数据管理

英文摘要： With the ever growing requirement for safety, videos captured by users, namely crowd-sourced videos along with CCTV videos are used as strong evidences for forensic applications. In this proposal, we aim at utilizing multi-sourced video data including CCTV videos and crowd-sourced videos for persistent target tracking in wide area. Current approaches of persistent tracking are based on multiple, fixed CCTV cameras which are not applicable if multi-sourced data are used. In this proposal, we present a comprehensive study of persistent target tracking using multi-sourced data. We fully utilize geospatial metadata of videos and propose a geospatial image filtering tool to select the most relevant video segments for target tracking. We also exploit the rich spatio-temporal context information in the video to enrich the representation of the target. The overall performance of persistent tracking is improved in terms of scalability, efficiency and tracking accuracy. This project will provide a solution to video surveillance in the new era of big data, which is both highly theoretical and has great potentials in real applications.

英文关键词： Computer Vision;Target Tracking;Mobile Video;Multiple Camera;Data Management