  Omnidirectional 360{\deg} images have found many promising and exciting
applications in computer vision, robotics and other fields, thanks to their
increasing affordability, portability and their 360{\deg} field of view. The
most common format for storing, processing and visualising 360{\deg} images is
equirectangular projection (ERP). However, the distortion introduced by the
nonlinear mapping from 360{\deg} image to ERP image 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{\deg} optical flow, as
the distortions need to be mitigated appropriately. In this paper, we propose a
360{\deg} 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 vertices, to incrementally refine the estimated 360{\deg} flow
fields even in the presence of large rotations. Our experiments demonstrate the
benefits of our proposed method both quantitatively and qualitatively.
