Mingze Yuan    Christian Richardt

University of Bath

British Machine Vision Conference (BMVC) 2021

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Abstract

Omnidirectional 360° images have found many promising and exciting applications in computer vision, robotics and other fields, thanks to their increasing affordability, portability and their 360° field of view. The most common format for storing, processing and visualising 360° images is equirectangular projection (ERP). However, the distortion introduced by the nonlinear mapping from 360° images to ERP images is still a barrier that holds back ERP images from being used as easily as conventional perspective images. This is especially relevant when estimating 360° optical flow, as the distortions need to be mitigated appropriately. In this paper, we propose a 360° optical flow method based on tangent images. Our method leverages gnomonic projection to locally convert ERP images to perspective images, and uniformly samples the ERP image by projection to a cubemap and regular icosahedron faces, to incrementally refine the estimated 360° flow fields even in the presence of large rotations. Our experiments demonstrate the benefits of our proposed method both quantitatively and qualitatively.

Bibtex

@InProceedings{360Flow,
  author    = {Mingze Yuan and Christian Richardt},
  title     = {360° Optical Flow using Tangent Images},
  booktitle = {BMVC},
  year      = {2021},
  url       = {https://richardt.name/360-flow/},
}