Efficient variants of the ICP algorithm
The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minim...
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| Published in | Proceedings Third International Conference on 3-D Digital Imaging and Modeling pp. 145 - 152 |
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| Main Authors | , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
2001
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| Subjects | |
| Online Access | Get full text |
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| Abstract | The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minimization strategy. We enumerate and classify many of these variants, and evaluate their effect on the speed with which the correct alignment is reached. In order to improve convergence for nearly-flat meshes with small features, such as inscribed surfaces, we introduce a new variant based on uniform sampling of the space of normals. We conclude by proposing a combination of ICP variants optimized for high speed. We demonstrate an implementation that is able to align two range images in a few tens of milliseconds, assuming a good initial guess. This capability has potential application to real-time 3D model acquisition and model-based tracking. |
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| AbstractList | The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variants of ICP have been proposed, affecting all phases of the algorithm from the selection and matching of points to the minimization strategy. We enumerate and classify many of these variants, and evaluate their effect on the speed with which the correct alignment is reached. In order to improve convergence for nearly-flat meshes with small features, such as inscribed surfaces, we introduce a new variant based on uniform sampling of the space of normals. We conclude by proposing a combination of ICP variants optimized for high speed. We demonstrate an implementation that is able to align two range images in a few tens of milliseconds, assuming a good initial guess. This capability has potential application to real-time 3D model acquisition and model-based tracking. |
| Author | Levoy, M. Rusinkiewicz, S. |
| Author_xml | – sequence: 1 givenname: S. surname: Rusinkiewicz fullname: Rusinkiewicz, S. organization: Stanford Univ., CA, USA – sequence: 2 givenname: M. surname: Levoy fullname: Levoy, M. |
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| SubjectTerms | Convergence Geometry Image sampling Iterative algorithms Iterative closest point algorithm Iterative methods Layout Minimization methods Rough surfaces Solid modeling |
| Title | Efficient variants of the ICP algorithm |
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