拓扑模型和特征学习的多摄像机接力跟踪策略  

Multi-camera relay-tracking strategies based on topological model and feature learning

作　　者：常发亮[1] 李江宝[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《吉林大学学报（工学版）》2013年第S1期330-334,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(60975025;61273277);山东省自然科学基金项目(ZR2011FM032);教育部留学回国人员科研启动基金项目(20101174);山东省机器人与制造自动化技术重点实验室开放基金项目(20111211)

摘　　要：为实现复杂大场景下目标跟踪的问题,提出了一种复杂大场景下基于拓扑模型和特征学习的多摄像机调度和目标接力跟踪策略。首先建立摄像机场景地图映射,通过实时背景估计确定目标的交接时刻和交接位置,然后建立多摄像机几何拓扑模型,给出了基于拓扑模型的多摄像机接力目标跟踪调度和交接算法,以及在跟踪过程中的特征学习方法,实现接力摄像机的快速调度和目标交接。实验结果表明,该方法可快速准确的完成多摄像机接力跟踪时的判断调度任务。In a video surveillance network system constructed by multi-cameras,when a target access to one camera's FOV(Field of Vision) from another's,it was a key problem to schedule the cameras correctly and to achieve reliable target handoff.Cameras scheduling and target handoff strategies were proposed based on topological model and feature learning that can be applied to multi-PTZ cameras relay target tracking system in a large and complex scene.First,a scene map model was constructed for Cameras,and a method based on real time background estimation was used to determine the handover time and position.Then a multi-camera geometric topological model was created,and,a scheduling handoff algorithm based on topological model and a feature learning algorithm were proposed to schedule the handover camera quickly and to complete the target handoff.The experimental results show that the proposed method can judge and schedule handover camera quickly and accurately in multi-cameras active tracking.

关 键 词：多摄像机 目标跟踪 拓扑模型 摄像机调度 特征学习 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]