Efficient variants of the ICP algorithm
Top Cited Papers
- 13 November 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 145-152
- https://doi.org/10.1109/im.2001.924423
Abstract
The ICP (Iterative Closest Point) algorithm is widely used for ge- ometric 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 se- lection 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. consider the accuracy of the final answer and the ability of ICP to reach the correct solution given "difficult" geometry. Our compar- isons suggest a combination of ICP variants that is able to align a pair of meshes in a few tens of milliseconds, significantly faster than most commonly-used ICP systems. The availability of such a real-time ICP algorithm may enable significant new applications in model-based tracking and 3D scanning. In this paper, we first present the methodology used for com- paring ICP variants, and introduce a number of test scenes used throughout the paper. Next, we summarize several ICP variants in each of the above six categories, and compare their convergence performance. As part of the comparison, we introduce the con- cept of normal-space-directed sampling, and show that it improves convergence in scenes involving sparse, small-scale surface fea- tures. Finally, we examine a combination of variants optimized for high speed.Keywords
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