3D object detection using a fast voxel-wise local spherical Fourier tensor transformation
Proceedings of the 32nd DAGM conference on Pattern recognition
Fast hypercomplex polar fourier analysis for image processing
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
Rotation-Invariant HOG Descriptors Using Fourier Analysis in Polar and Spherical Coordinates
International Journal of Computer Vision
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In this paper, polar and spherical Fourier analysis are defined as the decomposition of a function in terms of eigenfunctions of the Laplacian with the eigenfunctions being separable in the corresponding coordinates. The proposed transforms provide effective decompositions of an image into basic patterns with simple radial and angular structures. The theory is compactly presented with an emphasis on the analogy to the normal Fourier transform. The relation between the polar or spherical Fourier transform and the normal Fourier transform is explored. As examples of applications, rotation-invariant descriptors based on polar and spherical Fourier coefficients are tested on pattern classification problems.