Shape Registration with Spherical Cross Correlation

Abstract : We present a framework for shape alignment that generalizes several existing methods.We assume that the shape is a closed genus zero surface. Our framework requires a diffeomorphic surface mapping to the 2-sphere which preserves rotation. Our similarity measure is a global spherical cross-correlation function of surface-intrinsic scalar attributes, weighted by the cross-correlation of the parameterization distortion. The final similarity measure may be customized according to the surface- intrinsic scalar functions used in the application.
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Boris Gutman, Yalin Wang, Tony Chan, Paul M. Thompson, Arthur W. Toga. Shape Registration with Spherical Cross Correlation. 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Oct 2008, New-York, United States. pp.56-67. ⟨inria-00632874⟩

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