Scale-Adaptive ICP

SAHİLLİOĞLU Y., Kavan L.

Graphical Models, vol.116, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 116
  • Publication Date: 2021
  • Doi Number: 10.1016/j.gmod.2021.101113
  • Journal Name: Graphical Models
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, Geobase, INSPEC, zbMATH
  • Keywords: Pairwise registration, Shape registration, Shape alignment, Scale-adaptive, 3D POINT CLOUDS, REGISTRATION, ROBUST, ALGORITHM
  • Middle East Technical University Affiliated: Yes

Abstract

© 2021 Elsevier Inc.We present a new scale-adaptive ICP (Iterative Closest Point) method which aligns two objects that differ by rigid transformations (translations and rotations) and uniform scaling. The motivation is that input data may come in different scales (measurement units) which may not be known a priori, or when two range scans of the same object are obtained by different scanners. Classical ICP and its many variants do not handle this scale difference problem adequately. Our novel solution outperforms three different methods that estimate scale prior to alignment and a fourth method that, similar to ours, jointly optimizes for scale during the alignment.