Optical Flow Estimation using Fourier Mellin Transform
Authors: Huy Tho Ho and Roland Göcke
Presented by Huy Tho Ho at the IEEE Computer Society Conference on
Computer Vision and Pattern Recognition CVPR2008, Anchorage (AL),
USA, 24-26 June 2008
Abstract
In this paper, we propose a novel method of computing the optical flow
using the Fourier Mellin Transform (FMT). Each image in a sequence is
divided into a regular grid of patches and the optical flow is estimated
by calculating the phase correlation of each pair of co-sited patches
using the FMT. By applying the FMT in calculating the phase correlation,
we are able to estimate not only the pure translation, as limited in the
case of the basic phase correlation techniques, but also the scale and
rotation motion of image patches, i.e. full similarity transforms.
Moreover, the motion parameters of each patch can be estimated to subpixel
accuracy based on a recently proposed algorithm that uses a 2D sinc
function in fitting the data from the phase correlation output. We also
improve the estimation of the optical flow by presenting a method of
smoothing the field by using a vector weighted average filter. Finally,
experimental results, using publicly available data sets are presented,
demonstrating the accuracy and improvements of our method over previous
optical flow methods.
AUTHOR = {H.T. Ho and R. Goecke},
TITLE = {{Optical Flow Estimation using Fourier Mellin Transform}},
BOOKTITLE = {{Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR 2008}},
PUBLISHER = {IEEE Computer Society},
ADDRESS = {Anchorage (AL), USA},
MONTH = jun,
YEAR = 2008,
NOTE = {DOI: 10.1109/CVPR.2008.4587553}}