Local Non-Rigid Structure-From-Motion From Diffeomorphic Mappings

Shaifali Parashar, M. Salzmann, P. Fua
{"title":"Local Non-Rigid Structure-From-Motion From Diffeomorphic Mappings","authors":"Shaifali Parashar, M. Salzmann, P. Fua","doi":"10.1109/cvpr42600.2020.00213","DOIUrl":null,"url":null,"abstract":"We propose a new formulation to non-rigid structure-from-motion that only requires the deforming surface to preserve its differential structure. This is a much weaker assumption than the traditional ones of isometry or conformality. We show that it is nevertheless sufficient to establish local correspondences between the surface in two different images and therefore to perform point-wise reconstruction using only first-order derivatives. To this end, we formulate differential constraints and solve them algebraically using the theory of resultants. We will demonstrate that our approach is more widely applicable, more stable in noisy and sparse imaging conditions and much faster than earlier ones, while delivering similar accuracy. The code is available at https://github.com/cvlab-epfl/diff-nrsfm/.","PeriodicalId":6715,"journal":{"name":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","volume":"48 1","pages":"2056-2064"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cvpr42600.2020.00213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

We propose a new formulation to non-rigid structure-from-motion that only requires the deforming surface to preserve its differential structure. This is a much weaker assumption than the traditional ones of isometry or conformality. We show that it is nevertheless sufficient to establish local correspondences between the surface in two different images and therefore to perform point-wise reconstruction using only first-order derivatives. To this end, we formulate differential constraints and solve them algebraically using the theory of resultants. We will demonstrate that our approach is more widely applicable, more stable in noisy and sparse imaging conditions and much faster than earlier ones, while delivering similar accuracy. The code is available at https://github.com/cvlab-epfl/diff-nrsfm/.
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
微分同构映射的局部非刚性运动结构
我们提出了一种新的非刚性运动结构公式,该公式只要求变形表面保持其微分结构。这是一个比传统的等距或共形假设弱得多的假设。我们表明,尽管如此,在两个不同的图像中建立表面之间的局部对应关系是足够的,因此仅使用一阶导数进行逐点重建。为此,我们提出微分约束,并利用结果理论对其进行代数求解。我们将证明我们的方法更广泛适用,在嘈杂和稀疏成像条件下更稳定,并且比以前的方法快得多,同时提供相似的精度。代码可在https://github.com/cvlab-epfl/diff-nrsfm/上获得。
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
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery 3D Part Guided Image Editing for Fine-Grained Object Understanding SDC-Depth: Semantic Divide-and-Conquer Network for Monocular Depth Estimation Approximating shapes in images with low-complexity polygons PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation
×
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