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作 者:高飞[1,2,3] 王美珍 刘学军 王自然[4] GAO Fei;WANG Meizhen;LIU Xuejun;WANG Ziran(Key Laboratory of Virtual Geographic Environment(Nanjing Normal University),Ministry of Education,Nanjing 210023,China;State Key Laboratory of Cultivation Base of Geographic Environment Evolution(Jiangsu Province),Nanjing 210023,China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China;Nanjing Normal University Taizhou College,Taizhou 225300,China)
机构地区:[1]虚拟地理环境教育部重点实验室(南京师范大学),江苏南京210023 [2]江苏省地理环境演化国家重点实验室培育建设点,江苏南京210023 [3]江苏省地理信息资源开发与利用协同创新中心,江苏南京210023 [4]南京师范大学泰州学院,江苏泰州225300
出 处:《武汉大学学报(信息科学版)》2020年第3期362-373,共12页Geomatics and Information Science of Wuhan University
基 金:国家重点研发计划(2016YFE0131600);国家自然科学基金(41771420);江苏省高等学校自然科学研究面上项目(18KJB170007);江苏高校优势学科建设工程(164320H116);江苏省研究生科研与实践创新计划(KYCX17_1067).
摘 要:针对监控摄像机网络-路网的覆盖优化问题,提出了一种面向多优化目标的摄像机网络调度优化方法。该方法根据摄像机的感知特性,通过引入主光轴缓冲区系数来划分摄像机主光轴方向的活动范围,进而动态控制摄像机的调度规模及对特定摄像机、路段的覆盖应用偏好,并利用粒子群优化算法对路段覆盖数量、路网覆盖长度和摄像机调度数量等多个优化目标进行协同优化。实验结果表明,该方法具有较好的有效性和鲁棒性,同时考虑多个覆盖优化目标时,其可以提供摄像机网络的调度优化方案集合。As for the issue of coverage optimization of camera network and directional road network,a multi-objective coverage scheduling optimization method of camera network is proposed.Based on the sensing characteristics of cameras,the proposed method introduces the buffer parameter of main optical axis to divide the range of main optical axis,so as to control the scheduling number of cameras and the preference of specific camera and road section.Particle swarm optimization algorithm is used to optimize multiple coverage optimization objectives collaboratively,including the number of road sections covered,the length of road network covered and the number of cameras participating in scheduling.The experiment results demonstrate that the method can support multi-objective scheduling optimization and configuration of a camera network with good effectiveness and robustness.
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