{"title":"基于顺序蒙特卡罗算法的多目标跟踪与数据关联研究","authors":"Fan Lin-bo, K. Li, Wu Ying-cheng, Zhao Ming","doi":"10.1109/FBIE.2008.73","DOIUrl":null,"url":null,"abstract":"A new method based on sequential Monte Carlo algorithm is proposed for tracking multi-target and data association in non-linear system. The algorithm partitions the problem of multi-target tracking into two problems: single target tracking and data association. Single target tracking is implemented by using UKF and data association by using sequential Monte Carlo algorithm. Since Particle Filter has advantages in non-linear non-Gauss system, the proposed method performs well in the experiment.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Study of Multi-target Tracking and Data Association Based on Sequential Monte Carlo Algorithm\",\"authors\":\"Fan Lin-bo, K. Li, Wu Ying-cheng, Zhao Ming\",\"doi\":\"10.1109/FBIE.2008.73\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method based on sequential Monte Carlo algorithm is proposed for tracking multi-target and data association in non-linear system. The algorithm partitions the problem of multi-target tracking into two problems: single target tracking and data association. Single target tracking is implemented by using UKF and data association by using sequential Monte Carlo algorithm. Since Particle Filter has advantages in non-linear non-Gauss system, the proposed method performs well in the experiment.\",\"PeriodicalId\":415908,\"journal\":{\"name\":\"2008 International Seminar on Future BioMedical Information Engineering\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Seminar on Future BioMedical Information Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FBIE.2008.73\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Seminar on Future BioMedical Information Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FBIE.2008.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study of Multi-target Tracking and Data Association Based on Sequential Monte Carlo Algorithm
A new method based on sequential Monte Carlo algorithm is proposed for tracking multi-target and data association in non-linear system. The algorithm partitions the problem of multi-target tracking into two problems: single target tracking and data association. Single target tracking is implemented by using UKF and data association by using sequential Monte Carlo algorithm. Since Particle Filter has advantages in non-linear non-Gauss system, the proposed method performs well in the experiment.
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