• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

Recovery of global nonrigid motion: a model-based approach without point correspondences.

作者信息

Kumar S, Goldgof D

机构信息

Bell Laboratories, Holmdel, New Jersey 07733, USA.

出版信息

J Opt Soc Am A Opt Image Sci Vis. 2000 Sep;17(9):1617-26. doi: 10.1364/josaa.17.001617.

DOI:10.1364/josaa.17.001617
PMID:10975372
Abstract

We present a novel technique for the estimation of global nonrigid motion of an object's boundary without using point correspondences. A complete description of the motion of an object's boundary involves specifying a displacement vector at each point of the boundary. Such a description provides a large amount of information, which needs to be processed further for study of the global characteristics of the deformation. Nonrigid motion can be studied hierarchically in terms of global nonrigid motion and point-by-point local nonrigid motion. The technique presented gives a method for estimating a global affine or polynomial transformation between two object boundaries. The novelty of the technique lies in the fact that it does not use any point correspondences. Our method uses hyperquadric models to model the data and estimate the global deformation. We show that affine or polynomial transformation between two datasets can be recovered from the hyperquadric parameters. The usefulness of the technique is twofold. First, it paves the way for viewing nonrigid motion hierarchically in terms of global and local motion. Second, it can be used as a front end to other motion analysis techniques that assume small motion. For instance, most nonrigid motion analysis algorithms make some assumptions on the type of nonrigid motion (conformal motion, small motion, etc.) that are not always satisfied in practice. When the motion between two datasets is large, our algorithm can be used to estimate the affine transformation (which includes scale and shear) or a polynomial transformation between the two datasets, which can then be used to warp the first dataset closer to the second so as to satisfy the small-motion assumption. We present experimental results with real and synthetic two- and three-dimensional data.

摘要

相似文献

1
Recovery of global nonrigid motion: a model-based approach without point correspondences.
J Opt Soc Am A Opt Image Sci Vis. 2000 Sep;17(9):1617-26. doi: 10.1364/josaa.17.001617.
2
Estimation of contour motion and deformation for nonrigid object tracking.用于非刚性物体跟踪的轮廓运动和变形估计。
J Opt Soc Am A Opt Image Sci Vis. 2007 Aug;24(8):2109-21. doi: 10.1364/josaa.24.002109.
3
Fusion of physically-based registration and deformation modeling for nonrigid motion analysis.基于物理的配准和变形建模融合用于非刚体运动分析。
IEEE Trans Image Process. 2001;10(11):1659-69. doi: 10.1109/83.967394.
4
Artificial neural networks for 3-D motion analysis-Part II: Nonrigid motion.
IEEE Trans Neural Netw. 1995;6(6):1394-401. doi: 10.1109/72.471368.
5
Stratification approach for 3-D euclidean reconstruction of nonrigid objects from uncalibrated image sequences.从未校准图像序列进行非刚性物体三维欧几里得重建的分层方法。
IEEE Trans Syst Man Cybern B Cybern. 2008 Feb;38(1):90-101. doi: 10.1109/TSMCB.2007.910534.
6
Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint.使用具有不可压缩性约束的自由形式变形对乳腺磁共振图像进行体积保持非刚性配准。
IEEE Trans Med Imaging. 2003 Jun;22(6):730-41. doi: 10.1109/TMI.2003.814791.
7
On 3-D scene flow and structure recovery from multiview image sequences.关于从多视图图像序列中进行三维场景流和结构恢复
IEEE Trans Syst Man Cybern B Cybern. 2003;33(4):592-606. doi: 10.1109/TSMCB.2003.814284.
8
LPOT: Locality-Preserving Gromov-Wasserstein Discrepancy for Nonrigid Point Set Registration.LPOT:用于非刚性点集配准的局部保持Gromov-Wasserstein差异
IEEE Trans Neural Netw Learn Syst. 2024 Jul;35(7):9213-9225. doi: 10.1109/TNNLS.2022.3231652. Epub 2024 Jul 8.
9
A Robust Nonrigid Point Set Registration Method Based on Collaborative Correspondences.一种基于协作对应关系的鲁棒非刚性点集配准方法。
Sensors (Basel). 2020 Jun 7;20(11):3248. doi: 10.3390/s20113248.
10
Multiframe temporal estimation of cardiac nonrigid motion.心脏非刚性运动的多帧时间估计
IEEE Trans Image Process. 2000;9(4):651-65. doi: 10.1109/83.841941.