Towards Parameter Free Groupwise Non-Rigid Image Alignment

Ahmad Hashim Hussein Aal-Yhia, Paul Malcolm, Reyer Zwiggelaar, Bernard Tiddeman

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)

Abstract

Groupwise non-rigid image alignment is a difficult non-linear optimisation problem, involving many parameters and often large datasets. Previous methods have explored various metrics and optimisation strategies. Good results have been
previously achieved with simple metrics, but requiring complex optimisation, often with many unintuitive parameters that require careful tuning for each dataset. In this paper we restructure the problem to use a simpler, iterative optimisation algorithm, with very few free parameters. We demonstrate how to incorporate a stiffness constraint and how to tune the few remaining parameters. Results show that the method reliably aligns various datasets and demonstrates efficiency in terms performance and reduction of the computations.
Original languageEnglish
Pages245-252
Number of pages8
Publication statusPublished - 18 Jul 2018
EventInternational Conference on Computer Graphics, Visualization, Computer Vision and Image Processing (CGVCVIP) 2018 - Madrid, Spain
Duration: 18 Jul 201820 Jul 2018

Conference

ConferenceInternational Conference on Computer Graphics, Visualization, Computer Vision and Image Processing (CGVCVIP) 2018
Abbreviated titleCGVCVIP
Country/TerritorySpain
CityMadrid
Period18 Jul 201820 Jul 2018

Keywords

  • Non-Rigid Image Alignment
  • Groupwise Registration

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