Iterative most likely oriented point registration

Seth Billings, Russell Taylor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new algorithm for model based registration is presented that optimizes both position and surface normal information of the shapes being registered. This algorithm extends the popular Iterative Closest Point (ICP) algorithm by incorporating the surface orientation at each point into both the correspondence and registration phases of the algorithm. For the correspondence phase an efficient search strategy is derived which computes the most probable correspondences considering both position and orientation differences in the match. For the registration phase an efficient, closed-form solution provides the maximum likelihood rigid body alignment between the oriented point matches. Experiments by simulation using human femur data demonstrate that the proposed Iterative Most Likely Oriented Point (IMLOP) algorithm has a strong accuracy advantage over ICP and has increased ability to robustly identify a successful registration result.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
PublisherSpringer Verlag
Pages178-185
Number of pages8
EditionPART 1
ISBN (Print)9783319104034
DOIs
StatePublished - Jan 1 2014
Event17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States
Duration: Sep 14 2014Sep 18 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8673 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
CountryUnited States
CityBoston, MA
Period9/14/149/18/14

    Fingerprint

Keywords

  • Fisher distribution
  • PD tree
  • point cloud registration

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Billings, S., & Taylor, R. (2014). Iterative most likely oriented point registration. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings (PART 1 ed., pp. 178-185). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8673 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-319-10404-1_23