DocumentCode :
1642820
Title :
Direct 3D-rotation estimation from spherical images via a generalized shift theorem
Author :
Makadia, Ameesh ; Daniilidis, Kostas
Author_Institution :
GRASP Lab., Pennsylvania Univ., USA
Volume :
2
fYear :
2003
Abstract :
Omnidirectional images arising from 3D-motion of a camera contain persistent structures over a large variation of motions because of their large field of view. This persistence made appearance-based methods attractive for robot localization given reference views. Assuming that central omnidirectional images can be mapped to the sphere, the question is what are the underlying mappings of the sphere that can reflect a rotational camera motion. Given such a mapping, we propose a systematic way for finding invariance and the mapping parameters themselves based on the generalization of the Fourier transform. Using results from representation theory, we can generalize the Fourier transform to any homogeneous space with a transitively acting group. Such a case is the sphere with rotation as the acting group. The spherical harmonics of an image pair are related to each other through a shift theorem involving the irreducible representation of the rotation group. We show how to extract Euler angles using this theorem. We study the effect of the number of spherical harmonic coefficients as well as the effect of violation of appearance persistence in real imagery.
Keywords :
Fourier transforms; edge detection; harmonic analysis; image motion analysis; image representation; robot vision; 3D camera motion; Euler angle; Fourier transform generalization; direct 3D-rotation estimation; generalized shift theorem; harmonic analysis; image pair; invariance determination; irreducible representation; mapping parameter; motion variation; omnidirectional image; persistent structure; real imagery; reference view; robot localization; rotational camera motion; spherical harmonic coefficient; spherical image; Cameras; Fourier transforms; Image motion analysis; Laboratories; Layout; Motion estimation; Optical sensors; Robot localization; Robot vision systems; Spatiotemporal phenomena;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-1900-8
Type :
conf
DOI :
10.1109/CVPR.2003.1211473
Filename :
1211473
Link To Document :
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