Method for registration of 3D shapes without overlap for known 3D priors

Pengpeng Hu, Adrian Munteanu

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
10 Downloads (Pure)

Abstract

In 3D registration of point clouds, the goal is to find an optimal transformation that aligns the input shapes, provided that they have some overlap. Existing methods suffer from performance degradation when the overlapping ratio between the neighbouring point clouds is small. So far, there is no existing method that can be adopted for aligning shapes with no overlap. In this letter, to the best of knowledge, the first method for the registration of 3D shapes without overlap, assuming that the shapes correspond to partial views of a known semi-rigid 3D prior is presented. The method is validated and compared to existing methods on FAUST, which is a known dataset used for human body reconstruction. Experimental results show that this approach can effectively align shapes without overlap. Compared to existing state-of-the-art methods, this approach avoids iterative optimization and is robust to outliers and inherent inaccuracies induced by an initial rough alignment of the shapes.
Original languageEnglish
Pages (from-to)357-359
Number of pages3
JournalElectronics Letters
Volume57
Issue number9
Early online date15 Mar 2021
DOIs
Publication statusPublished - 23 Apr 2021
Externally publishedYes

Bibliographical note

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Funder

Innoviris. Grant Number: BRGRD24

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