Gianfranco Doretto / Publications

A frequency domain technique for range data registration

Lucchese, L., Doretto, G., and Cortelazzo, G. M.
A frequency domain technique for range data registration
IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(11):1468–1484, November 2002.

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Abstract

This work introduces an original method for registering pairs of 3D views consisting of range data sets which operates in the frequency domain. The Fourier transform allows the decoupling of the estimate of the rotation parameters from the estimate of the translation parameters, our algorithm exploits this well- known property by suggesting a three-step procedure. The rotation parameters are estimated by the first two steps through convenient representations and projections of the Fourier transforms' magnitudes and the translational displacement is recovered by the third step by means of a standard phase correlation technique after compensating one of the two views for rotation. The performance of the algorithm, which is well-suited for unsupervised registration, is clearly assessed through extensive testing with several objects and shows that good and robust estimates of 3D rigid motion are achievable. Our algorithm can be used as a prealignment tool for more accurate space-domain registration techniques, like the ICP algorithm.

BibTeX

@Article{luccheseDC02IEEEtpami,
  Title                    = {A frequency domain technique for range data registration},
  Author                   = {Lucchese, L. and Doretto, G. and Cortelazzo, G. M.},
  Journal                  = IEEEtpami,
  Year                     = {2002},
  Month                    = nov,
  Number                   = {11},
  Pages                    = {1468--1484},
  Volume                   = {24},
  Abstract                 = {This work introduces an original method for registering pairs of 3D views consisting of range data sets which operates in the frequency domain. The Fourier transform allows the decoupling of the estimate of the rotation parameters from the estimate of the translation parameters, our algorithm exploits this well- known property by suggesting a three-step procedure. The rotation parameters are estimated by the first two steps through convenient representations and projections of the Fourier transforms' magnitudes and the translational displacement is recovered by the third step by means of a standard phase correlation technique after compensating one of the two views for rotation. The performance of the algorithm, which is well-suited for unsupervised registration, is clearly assessed through extensive testing with several objects and shows that good and robust estimates of 3D rigid motion are achievable. Our algorithm can be used as a prealignment tool for more accurate space-domain registration techniques, like the ICP algorithm.},
  Bib2html_pubtype         = {Journals},
  Bib2html_rescat          = {3D Object modeling},
  Doi                      = {10.1109/TPAMI.2002.1046160},
  File                     = {luccheseDC02IEEEtpami.pdf:doretto\\journal\\luccheseDC02IEEEtpami.pdf:PDF;luccheseDC02IEEEtpami.pdf:doretto\\journal\\luccheseDC02IEEEtpami.pdf:PDF},
  ISSN                     = {0162-8828},
  Keywords                 = {Fourier transforms, frequency-domain analysis, image motion analysis, image registration, parameter estimation},
  Owner                    = {doretto},
  Timestamp                = {2007.01.19}
}