{"title":"A PSO-based algorithm for video networks planning optimization","authors":"Jiang Peng, J. Weidong","doi":"10.1109/CISP.2013.6743970","DOIUrl":null,"url":null,"abstract":"In this paper we examine issues of deploying a camera network in a complex environment with obstacles. A camera network is composed of a distributed collection of cameras, each of which has sensing and communicating capabilities. To deploy such camera network, we present a kinetics based particle swarm optimization (PSO) approach. By introducing a kinetics-constraint factor to standard PSO, the fields are covered such that each camera is repelled by both other cameras and obstacles, thereby forcing the network to spread throughout the monitored area. The coverage enhancement is fulfilled by finding an optimal orientation for each camera, guided by PSO optimizer. Experimental results show our method is able to achieve higher coverage rate than conventional methods.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 6th International Congress on Image and Signal Processing (CISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2013.6743970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper we examine issues of deploying a camera network in a complex environment with obstacles. A camera network is composed of a distributed collection of cameras, each of which has sensing and communicating capabilities. To deploy such camera network, we present a kinetics based particle swarm optimization (PSO) approach. By introducing a kinetics-constraint factor to standard PSO, the fields are covered such that each camera is repelled by both other cameras and obstacles, thereby forcing the network to spread throughout the monitored area. The coverage enhancement is fulfilled by finding an optimal orientation for each camera, guided by PSO optimizer. Experimental results show our method is able to achieve higher coverage rate than conventional methods.