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, affcting all phases of the algorithm from the selection and matching of points to the minimization strategy. We enumerate and classifjl many of these variants, and evaluate their efSect on the speed with which the correct alignment is reached. In order to improve convergence for nearly-gat meshes with small features, such as inscribed sugaces, 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 3 0 model acquisition and model-based tracking.
There are many variants of ICP REF .
Efficient variants of the ICP algorithm
Proceedings Third International Conference on 3-D Digital Imaging and Modeling
Proceedings Third International Conference on 3-D Digital Imaging and Modeling
Computer Science