Rotation estimation from spherical images

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.