基于粒子群优化的视频传感器网络覆盖增强算法  

PSO-based Video Sensor Networks Coverage Optimization Algorithm

作　　者：蒋鹏[1] 金炜东[1] 秦娜[1] 唐鹏[1] 周艳[1] 

机构地区：[1]西南交通大学电气工程学院,成都610031

出　　处：《计算机科学》2014年第4期57-61,共5页Computer Science

基　　金：中央高校基本科研业务费专项资金项目(SWJTU12CX027);国家自然科学基金(60971103;61134002)资助

摘　　要：以提高视频传感器网络的覆盖率为目标,针对摄像机的有向感知特性,提出了一种基于改进粒子群优化的视频传感器网络监控区域增强算法。通过分析监控区域中摄像机部署位置关系及有向感知性,构建了反映摄像机相互作用的虚拟力,并引入了基于虚拟力的粒子群导向因子。基于该导向因子,粒子群算法能够有导向地逐步快速地接近优化目标,避免了反复调整过程,提高了优化速度。一系列仿真结果验证了该算法能够在复杂的监控区域场景下大幅提高覆盖率,其性能优于传统方法。To improve the video sensor network coverage,a novel particle swam optimization （PSO） based camera network planning algorithm was proposed according to the directional features of Pan-Tilt-Zoom camera.The virtual forces are used to simulate the planning location correlation among cameras.Then the virtual force factor is added as a speedup parameter to guide PSO to maximize coverage.This virtual force factor based PSO can reduce the PSO optimization time and improve the coverage without back and forth adjustment.A serial of simulated experimental results show our method is able to achieve higher coverage rote than conventional methods in complex scene.

关 键 词：摄像头网络 粒子群优化 覆盖增强 虚拟力 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]