1. A Shape-Based Weighting Strategy Applied to the Covariance Estimation on ICP.
- Author
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Yamada, F. A. A., Cejnog, L. W. X., Vieira, M. B., and da Silva, R. L. S.
- Subjects
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ALGORITHMS , *COMPUTATIONAL geometry , *MATRICES (Mathematics) , *TENSOR algebra , *NOISE - Abstract
In the pairwise rigid registration problem, we need to find a rigid transformation that aligns two point clouds. The classical and most common solution is the Iterative Closest Point (ICP) algorithm. However, the ICP and many of its variants require that the point clouds are already coarsely aligned. We present in this paper a method named Shape-based Weighting Covariance Iterative Closest Point (SWC-ICP) which improves the possibility to correctly align two point clouds, regardless of the initial pose, even when they are only partially overlapped, or in the presence of noise and outliers. It benefits from the local geometry of the points, encoded in second-order orientation tensors, to provide a second correspondences set to the ICP. The cross-covariance matrix computed from this set is combined with the usual cross-covariance matrix, following a heuristic strategy. In order to compare our method with some recent approaches, we present a detailed evaluation protocol to rigid registration. Results show that the SWC-ICP is among the best compared methods, with a better performance in situations of wide angular displacement of noisy point clouds. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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