Rotation recovery from spherical images without correspondences

This paper addresses the problem of rotation estimation directly from images defined on the sphere and without correspondence. The method is particularly useful for the alignment of large rotations and has potential impact on 3D shape alignment. The foundation of the method lies in the fact that the...

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Détails bibliographiques
Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1998. - 28(2006), 7 vom: 15. Juli, Seite 1170-5
Auteur principal: Makadia, Ameesh (Auteur)
Autres auteurs: Daniilidis, Kostas
Format: Article
Langue:English
Publié: 2006
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Journal Article Research Support, U.S. Gov't, Non-P.H.S.
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520 |a This paper addresses the problem of rotation estimation directly from images defined on the sphere and without correspondence. The method is particularly useful for the alignment of large rotations and has potential impact on 3D shape alignment. The foundation of the method lies in the fact that the spherical harmonic coefficients undergo a unitary mapping when the original image is rotated. The correlation between two images is a function of rotations and we show that it has an SO(3)-Fourier transform equal to the pointwise product of spherical harmonic coefficients of the original images. The resolution of the rotation space depends on the bandwidth we choose for the harmonic expansion and the rotation estimate is found through a direct search in this 3D discretized space. A refinement of the rotation estimate can be obtained from the conservation of harmonic coefficients in the rotational shift theorem. A novel decoupling of the shift theorem with respect to the Euler angles is presented and exploited in an iterative scheme to refine the initial rotation estimates. Experiments show the suitability of the method for large rotations and the dependence of the method on bandwidth and the choice of the spherical harmonic coefficients 
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