深度估计,以管理视觉伺服期间的视觉信号损失与3自由度相机

A. D. Petiteville, V. Cadenat, M. Courdesses
{"title":"深度估计,以管理视觉伺服期间的视觉信号损失与3自由度相机","authors":"A. D. Petiteville, V. Cadenat, M. Courdesses","doi":"10.1109/ECMSM.2013.6648953","DOIUrl":null,"url":null,"abstract":"This paper deals with the problem of estimating the visual features during a vision-based navigation task when a temporary total occlusion occurs. The proposed approach relies on an existent specific algorithm. However, to be efficient, this algorithm requires highly precise initial values for both the image features and their depth. Thus, our objective is to design a predictor/estimator pair able to provide an accurate estimation of the depth value, even when the visual data are noisy. We also aim at obtaining a method reducing the implementation complexity while preserving performances. The obtained results show the efficiency and the interest of our technique.","PeriodicalId":174767,"journal":{"name":"2013 IEEE 11th International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics","volume":"1 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Depth estimation to manage visual signal loss during visual servoing with a 3 DOF camera\",\"authors\":\"A. D. Petiteville, V. Cadenat, M. Courdesses\",\"doi\":\"10.1109/ECMSM.2013.6648953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the problem of estimating the visual features during a vision-based navigation task when a temporary total occlusion occurs. The proposed approach relies on an existent specific algorithm. However, to be efficient, this algorithm requires highly precise initial values for both the image features and their depth. Thus, our objective is to design a predictor/estimator pair able to provide an accurate estimation of the depth value, even when the visual data are noisy. We also aim at obtaining a method reducing the implementation complexity while preserving performances. The obtained results show the efficiency and the interest of our technique.\",\"PeriodicalId\":174767,\"journal\":{\"name\":\"2013 IEEE 11th International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics\",\"volume\":\"1 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 11th International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECMSM.2013.6648953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 11th International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECMSM.2013.6648953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文研究了基于视觉的导航任务中出现暂时全遮挡时的视觉特征估计问题。该方法依赖于已有的特定算法。然而,为了提高效率,该算法需要高度精确的图像特征和深度的初始值。因此,我们的目标是设计一个预测器/估计器对,即使在视觉数据有噪声的情况下,也能提供对深度值的准确估计。我们的目标是找到一种在保证性能的同时降低实现复杂度的方法。所得结果表明了该方法的有效性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Depth estimation to manage visual signal loss during visual servoing with a 3 DOF camera
This paper deals with the problem of estimating the visual features during a vision-based navigation task when a temporary total occlusion occurs. The proposed approach relies on an existent specific algorithm. However, to be efficient, this algorithm requires highly precise initial values for both the image features and their depth. Thus, our objective is to design a predictor/estimator pair able to provide an accurate estimation of the depth value, even when the visual data are noisy. We also aim at obtaining a method reducing the implementation complexity while preserving performances. The obtained results show the efficiency and the interest of our technique.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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