An algorithm to map asymmetries of bilateral objects in point clouds

Benoit Combes, Robin Hennessy, John Waddington, Neil Roberts, Sylvain Prima

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

Abstract

We present a method to automatically quantify the local asymmetries of bilateral structures in point clouds. The method relies on the robust computation of the approximate symmetry plane of the object under study. This plane is defined as the minimiser of a criterion, based on a M-estimator and devised to reduce the influence of asymmetrical features of the object. An algorithm is then proposed to minimise this criterion. Once the algorithm has converged, the residual distances between the points and their symmetrical counterparts quantify the local asymmetries, yielding a 3D asymmetry map. We show the algorithm to be accurate, with a high capture range, on an ideal, perfectly symmetrical dataset. We investigate its robustness and accuracy properties on highly corrupted datasets. We also evaluate the accuracy of the obtained 3D maps using ground truth datasets where the asymmetries are known. Finally, we propose several original applications of this method on real data.

Original languageEnglish
Title of host publication2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1139-1142
Number of pages4
ISBN (Print)978-1-4244-2002-5
Publication statusPublished - 2008
Event5th IEEE International Symposium on Biomedical Imaging - Paris, France
Duration: 14 May 200817 May 2008

Publication series

NameIEEE International Symposium on Biomedical Imaging
PublisherIEEE
ISSN (Print)1945-7928

Conference

Conference5th IEEE International Symposium on Biomedical Imaging
CountryFrance
Period14/05/0817/05/08

Keywords

  • symmetry
  • asymmetry
  • point clouds
  • surfaces
  • 3D mapping
  • face
  • skull
  • SYMMETRY
  • SHAPE
  • SCHIZOPHRENIA
  • PLANE

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