{"title":"A novel target tracking method based on scale-invariant feature transform in imagery","authors":"Huang Qinglong, Yun Zhang, Ling Hongbo, Wangbin, Feng Tianjiao","doi":"10.1109/RSIP.2017.7958801","DOIUrl":null,"url":null,"abstract":"In this paper, a novel effective method based on Scale-invariant feature transform in Imagery to realize Target tracking, where the discriminating process is improved through Image Matching Processing. It is the first time that the problem of tracking in Imaging processing, contrasted with traditional methods in data processing. It can track target for clutter. Simulation results show that the proposed method has advantages in the efficiency and accuracy under the circumstances with heavy clutter and large measurement error.","PeriodicalId":262222,"journal":{"name":"2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RSIP.2017.7958801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a novel effective method based on Scale-invariant feature transform in Imagery to realize Target tracking, where the discriminating process is improved through Image Matching Processing. It is the first time that the problem of tracking in Imaging processing, contrasted with traditional methods in data processing. It can track target for clutter. Simulation results show that the proposed method has advantages in the efficiency and accuracy under the circumstances with heavy clutter and large measurement error.