Cited by 1,560Medical Image Segmentation Techniques3D Shape Modeling and AnalysisAdvanced Image and Video Retrieval Techniques

A new point matching algorithm for non-rigid registration

Chui, Haili, Rangarajan, Anand·2003·Computer Vision and Image Understanding

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Crossref · 10.1016/s1077-3142(03)00009-2

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56 of 56 references verified0 citation errors · 0 not checkable

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  • Schulman et al. propose to transfer a demonstration trajectory using non-rigid registration between the observed scene and a demonstrated scene, using Thin Plate Spline Robust Point Matching on point clouds.

    “Schulman et al. (2016) [116], on the other hand, propose to transfer the demonstration trajectory using non-rigid registration between the observed scene and a demonstrated scene. They conduct the registration using the Thin Plate Spline Robust Point Matching (TPS-RPM) approach proposed by Chui and Rangarajan (2003) [117] on the scene represented as point clouds.”
  • Although many non-rigid deformation models are different in formulation, they all have one common characteristic: they all try to preserve some kind of smoothness.

    “Although many of these non-rigid deformation models are different in terms of formulation, they all have one common characteristic.Whether they use adjacency similarity, gradient or Laplacian fields [28] (first-order), thin-plate splines [35] (second-order), or various regularizers (Section 4.2.6), they all try to preserve some kind of smoothness.”

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Authors
Chui, H., & Rangarajan, A.
Affiliations
University of Florida (US)
Corresponding author
Rangarajan, Anand
Venue
Computer Vision and Image Understanding
Publisher
Elsevier BV
Published
2003-02
Volume
89
Issue
2-3
Pages
114-141
ISSN
1077-3142 (ISSN-L)
OpenAlex
W2171490473
Cited by
1,560
References
56
Citations by year
2026: 24 · 2025: 20 · 2024: 34 · 2023: 36 · 2022: 50 · 2021: 52 · 2020: 66 · 2019: 79 · 2018: 75 · 2017: 85 · 2016: 111 · 2015: 121 · 2014: 112 · 2013: 86 · 2012: 86
FWCI
42.12
Type
journal article
Language
en
Open access
closed
Locations
Computer Vision and Image Understanding (publishedVersion)
Funders
National Science Foundation
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Physical Sciences › Engineering › Computational Mechanics › 3D Shape Modeling and Analysis
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
Keywords
non-rigid registration, point matching, feature-based registration, correspondence problem, outlier removal, thin-plate splines, cortical anatomy, brain mapping

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