物理建模及距离和强度边缘数据的组合

Zhang G.H., Wallace A.
{"title":"物理建模及距离和强度边缘数据的组合","authors":"Zhang G.H.,&nbsp;Wallace A.","doi":"10.1006/ciun.1993.1038","DOIUrl":null,"url":null,"abstract":"<div><p>We present a method for semantic labelling of edges and reconstruction of range data by fusion of registered range and intensity images. An initial set of edge labels is derived using a physical model of object geometry and shading. A final edge classification and range reconstruction are obtained using Bayesian estimation within coupled Markov random fields employing constraints of surface smoothness and edge continuity. The approach is demonstrated on synthetic and real source data, obtained from an active laser rangefinder.</p></div>","PeriodicalId":100350,"journal":{"name":"CVGIP: Image Understanding","volume":"58 2","pages":"Pages 191-220"},"PeriodicalIF":0.0000,"publicationDate":"1993-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/ciun.1993.1038","citationCount":"20","resultStr":"{\"title\":\"Physical Modeling and Combination of Range and Intensity Edge Data\",\"authors\":\"Zhang G.H.,&nbsp;Wallace A.\",\"doi\":\"10.1006/ciun.1993.1038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We present a method for semantic labelling of edges and reconstruction of range data by fusion of registered range and intensity images. An initial set of edge labels is derived using a physical model of object geometry and shading. A final edge classification and range reconstruction are obtained using Bayesian estimation within coupled Markov random fields employing constraints of surface smoothness and edge continuity. The approach is demonstrated on synthetic and real source data, obtained from an active laser rangefinder.</p></div>\",\"PeriodicalId\":100350,\"journal\":{\"name\":\"CVGIP: Image Understanding\",\"volume\":\"58 2\",\"pages\":\"Pages 191-220\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1006/ciun.1993.1038\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CVGIP: Image Understanding\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1049966083710387\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CVGIP: Image Understanding","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1049966083710387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

摘要

提出了一种边缘语义标记和距离数据重建的方法。使用物体几何和阴影的物理模型派生出一组初始边缘标签。利用表面光滑性和边缘连续性约束,利用耦合马尔可夫随机场内的贝叶斯估计得到最终的边缘分类和距离重建。该方法在主动式激光测距仪的合成源数据和真实源数据上进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Physical Modeling and Combination of Range and Intensity Edge Data

We present a method for semantic labelling of edges and reconstruction of range data by fusion of registered range and intensity images. An initial set of edge labels is derived using a physical model of object geometry and shading. A final edge classification and range reconstruction are obtained using Bayesian estimation within coupled Markov random fields employing constraints of surface smoothness and edge continuity. The approach is demonstrated on synthetic and real source data, obtained from an active laser rangefinder.

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