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Point Set Registration: Coherent Point Drift

IEEE Transactions on Pattern Analysis and Machine Intelligence

Andriy Myronenko, None Xubo Song

Citations:

2531

References:

55

Abstract
Point set registration is a key component in many computer vision tasks. The goal of point set registration is to assign correspondences between two sets of points and to recover the transformation that maps one point set to the other. Multiple factors, including an unknown nonrigid spatial transformation, large dimensionality of point set, noise, and outliers, make the point set registration a ch...
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Keywords
Point set registration
Rigid transformation
Outlier
Centroid
Algorithm
Mixture model
Transformation (genetics)
Artificial intelligence
Mathematics
Noise (video)
Expectation–maximization algorithm
Computer science
Pattern recognition (psychology)
Point (geometry)
Image (mathematics)
Geometry
Maximum likelihood
Biochemistry
Chemistry
Statistics
Gene
2010
Article

Open Access

Institution

Dept. of Sci. & Eng., Oregon Health & Sci. Univ., Beaverton, OR, USA

Publisher

IEEE Computer Society

2-Y Citation Average

14.63

DOI

https://doi.org/10.1109/tpami.2010.46

Language

en

Country

United States

pdf file
Point Set Registration: Coherent Point Drift
pdf file

Point Set Registration: Coherent Point Drift

IEEE Transactions on Pattern Analysis and Machine Intelligence

Andriy Myronenko, None Xubo Song

Citations:

2531

References:

55

Abstract
Point set registration is a key component in many computer vision tasks. The goal of point set registration is to assign correspondences between two sets of points and to recover the transformation that maps one point set to the other. Multiple factors, including an unknown nonrigid spatial transformation, large dimensionality of point set, noise, and outliers, make the point set registration a ch...
See More
View PDF
Keywords
Point set registration
Rigid transformation
Outlier
Centroid
Algorithm
Mixture model
Transformation (genetics)
Artificial intelligence
Mathematics
Noise (video)
Expectation–maximization algorithm
Computer science
Pattern recognition (psychology)
Point (geometry)
Image (mathematics)
Geometry
Maximum likelihood
Biochemistry
Chemistry
Statistics
Gene
2010
Article

Open Access

Institution

Dept. of Sci. & Eng., Oregon Health & Sci. Univ., Beaverton, OR, USA

Publisher

IEEE Computer Society

2-Y Citation Average

14.63

DOI

https://doi.org/10.1109/tpami.2010.46

Language

en

Country

United States

pdf file