An Approach to Robust ICP Initialization

Alexander Kolpakov; Michael Werman

doi:10.1109/TPAMI.2023.3287468

An Approach to Robust ICP Initialization

Alexander Kolpakov, Michael Werman^*

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

In this note, we propose an approach to initialize the Iterative Closest Point (ICP) algorithm to match unlabelled point clouds related by rigid transformations. The method is based on matching the ellipsoids defined by the points' covariance matrices and then testing the various principal half-axes matchings that differ by elements of a finite reflection group. We derive bounds on the robustness of our approach to noise and numerical experiments confirm our theoretical findings.

Original language	English
Pages (from-to)	12685-12691
Number of pages	7
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	45
Issue number	10
DOIs	https://doi.org/10.1109/TPAMI.2023.3287468
State	Published - 1 Oct 2023

Bibliographical note

Publisher Copyright:
© 1979-2012 IEEE.

Keywords

ICP
image registration
image stitching

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10.1109/TPAMI.2023.3287468

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An Approach to Robust ICP Initialization

Abstract

Bibliographical note

Keywords

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