Grid Based Fusion & Tracking

O. Aycard, A. Spalanzani, J. Burlet, Chiara Fulgenzi, Trung-Dung Vu, D. Raulo, M. Yguel
{"title":"Grid Based Fusion & Tracking","authors":"O. Aycard, A. Spalanzani, J. Burlet, Chiara Fulgenzi, Trung-Dung Vu, D. Raulo, M. Yguel","doi":"10.1109/ITSC.2006.1706782","DOIUrl":null,"url":null,"abstract":"In this paper, we detail the perception system designed and developed in our group to track multi-objects. This system is divided in two parts: a fusion part to fusion the data given by different sensors and a tracking part to sequentially estimate the position of each object present in the environment and to determine the number of objects. We also present how this system has been used in the context of vulnerable safety in a car park. Finally, some experimental results are presented","PeriodicalId":184458,"journal":{"name":"International Conference on Intelligent Transportation Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2006.1706782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

In this paper, we detail the perception system designed and developed in our group to track multi-objects. This system is divided in two parts: a fusion part to fusion the data given by different sensors and a tracking part to sequentially estimate the position of each object present in the environment and to determine the number of objects. We also present how this system has been used in the context of vulnerable safety in a car park. Finally, some experimental results are presented
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于网格的融合与跟踪
在本文中,我们详细介绍了我们小组设计和开发的用于跟踪多目标的感知系统。该系统分为两部分:融合部分用于融合不同传感器给出的数据;跟踪部分用于顺序估计环境中存在的每个物体的位置并确定物体的数量。我们还介绍了该系统如何在停车场的脆弱安全环境中使用。最后给出了一些实验结果
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Combining K-means method and complex network analysis to evaluate city mobility Goal-Driven Context-Aware Data Filtering in IoT-Based Systems Vision-Based Driver Assistance Systems: Survey, Taxonomy and Advances An Improved FastSLAM Algorithm for Autonomous Vehicle Based on the Strong Tracking Square Root Central Difference Kalman Filter Planning of High-Level Maneuver Sequences on Semantic State Spaces
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1