Super-Fibonacci Spirals: Fast, Low-Discrepancy Sampling of SO(3)

Marc Alexa; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, pp. 8291-8300

Abstract

Super-Fibonacci spirals are an extension of Fibonacci spirals, enabling fast generation of an arbitrary but fixed number of 3D orientations. The algorithm is simple and fast. A comprehensive evaluation comparing to other methods shows that the generated sets of orientations have low discrepancy, minimal spurious components in the power spectrum, and almost identical Voronoi volumes. This makes them useful for a variety of applications in vision, robotics, machine learning, and in particular Monte Carlo sampling.

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[bibtex]
@InProceedings{Alexa_2022_CVPR, author = {Alexa, Marc}, title = {Super-Fibonacci Spirals: Fast, Low-Discrepancy Sampling of SO(3)}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2022}, pages = {8291-8300} }