Adaptive particle filter based pose estimation using a monocular camera model

Mohammad Goli, A. Ghanbari, F. Janabi-Sharifi, Ghader Karimian Khosroshahi
{"title":"Adaptive particle filter based pose estimation using a monocular camera model","authors":"Mohammad Goli, A. Ghanbari, F. Janabi-Sharifi, Ghader Karimian Khosroshahi","doi":"10.1109/ISOT.2010.5687313","DOIUrl":null,"url":null,"abstract":"Camera full pose estimation using only a monocular camera model is an important topic in the field of visual servoing. In this paper a simple adaptive method for updating the weights of particle filter is proposed. Using this method, the efficiency of particle filter in estimating the full pose of camera is improved. Results of the proposed method are compared with those of generic particle filter (PF) and EKF under the same condition through an intensive computer simulation.","PeriodicalId":91154,"journal":{"name":"Optomechatronic Technologies (ISOT), 2010 International Symposium on : 25-27 Oct. 2010 : [Toronto, ON]. International Symposium on Optomechatronic Technologies (2010 : Toronto, Ont.)","volume":"4 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optomechatronic Technologies (ISOT), 2010 International Symposium on : 25-27 Oct. 2010 : [Toronto, ON]. International Symposium on Optomechatronic Technologies (2010 : Toronto, Ont.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISOT.2010.5687313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Camera full pose estimation using only a monocular camera model is an important topic in the field of visual servoing. In this paper a simple adaptive method for updating the weights of particle filter is proposed. Using this method, the efficiency of particle filter in estimating the full pose of camera is improved. Results of the proposed method are compared with those of generic particle filter (PF) and EKF under the same condition through an intensive computer simulation.
基于自适应粒子滤波的单目摄像机姿态估计模型
单目摄像机模型下的摄像机全姿态估计是视觉伺服领域的一个重要研究课题。本文提出了一种简单的自适应更新粒子滤波器权值的方法。利用该方法,提高了粒子滤波估计相机全位姿的效率。通过计算机仿真,将所提方法与通用粒子滤波(PF)和EKF在相同条件下的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信