Rotation Recovery from Spherical Images without Correspondences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Correspondence-Free Determination of the Affine Fundamental Matrix
IEEE Transactions on Pattern Analysis and Machine Intelligence
Conformal spherical representation of 3D genus-zero meshes
Pattern Recognition
An Approximate and Efficient Method for Optimal Rotation Alignment of 3D Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Correspondence-free Structure from Motion
International Journal of Computer Vision
View-based robot localization using spherical harmonics: concept and first experimental results
Proceedings of the 29th DAGM conference on Pattern recognition
Spherical Correlation of Visual Representations for 3D Model Retrieval
International Journal of Computer Vision
Spectral registration of noisy sonar data for underwater 3D mapping
Autonomous Robots
New 3d fourier descriptors for genus-zero mesh objects
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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Robotic navigation algorithms increasingly make use of the panoramic field of view provided by omnidirectional images to assist with localization tasks. Since the images taken by a particular class of omnidirectional sensors can be mapped to the sphere, the problem of attitude estimation arising from 3D rotations of the camera can be treated as a problem of estimating rotations between spherical images. Recently it has been shown that direct signal processing techniques are effective tools in handling rotations of the sphere, but are limited when the signal is altered by larger rotations of omnidirectional cameras. We present an effective solution to the attitude estimation problem under large rotations. Our approach utilizes a Shift Theorem for the Spherical Fourier Transform to produce a solution in the spectral domain.