Determining characteristic views of a 3D object by visual hulls and Hausdorff distance

A. Theetten, Jean-Philippe Vandeborre, M. Daoudi
{"title":"Determining characteristic views of a 3D object by visual hulls and Hausdorff distance","authors":"A. Theetten, Jean-Philippe Vandeborre, M. Daoudi","doi":"10.1109/3DIM.2005.31","DOIUrl":null,"url":null,"abstract":"Nowadays, with the exponential growing of 3D object representations in private databases or on the web, it is all the more required to match these objects from some views. To improve the results of their matching, we work on the characteristic views of an object. The aim of this study is to find how many characteristic views are required and what relative positions are optimal. This is the reason why the visual hulls are used. From some 2D masks, the nearest possible 3D mesh from the original object is computed. OpenGL views are used to build the visual hulls of 3D models from a given collection and then the distance between the visual hulls and the models are measured thanks to the Hausdorff distance. Then the best view parameters are deduced to reduce the distance. These shots show that three orthogonal views give results very close to the ones given by twelve views on a isocahedron. Some other results on the view resolution and the field of view are discussed.","PeriodicalId":170883,"journal":{"name":"Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DIM.2005.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Nowadays, with the exponential growing of 3D object representations in private databases or on the web, it is all the more required to match these objects from some views. To improve the results of their matching, we work on the characteristic views of an object. The aim of this study is to find how many characteristic views are required and what relative positions are optimal. This is the reason why the visual hulls are used. From some 2D masks, the nearest possible 3D mesh from the original object is computed. OpenGL views are used to build the visual hulls of 3D models from a given collection and then the distance between the visual hulls and the models are measured thanks to the Hausdorff distance. Then the best view parameters are deduced to reduce the distance. These shots show that three orthogonal views give results very close to the ones given by twelve views on a isocahedron. Some other results on the view resolution and the field of view are discussed.
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
通过视觉船体和豪斯多夫距离确定3D物体的特征视图
如今,随着私有数据库或网络上的3D对象表示呈指数级增长,从某些角度匹配这些对象的需求越来越大。为了改进它们的匹配结果,我们对一个对象的特征视图进行了研究。本研究的目的是找出需要多少个特征视图以及什么相对位置是最优的。这就是为什么使用视觉船体的原因。从一些2D遮罩中,计算最接近原始对象的可能3D网格。OpenGL视图用于从给定集合中构建3D模型的视觉外壳,然后利用Hausdorff距离测量视觉外壳与模型之间的距离。然后推导出最佳视点参数以减小距离。这些照片表明,三个正交的视图所得到的结果非常接近于在一个等面体上12个视图所得到的结果。讨论了其他一些关于视场分辨率和视场的结果。
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
A complete U-V-disparity study for stereovision based 3D driving environment analysis Simultaneous determination of registration and deformation parameters among 3D range images 3D digitization of a large model of imperial Rome Evaluating collinearity constraint for automatic range image registration Realistic human head modeling with multi-view hairstyle reconstruction
×
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