  We address the problem of motion estimation in images operating in the
frequency domain. A method is presented which extends phase correlation to
handle multiple motions present in an area. Our scheme is based on a novel
Bilateral-Phase Correlation (BLPC) technique that incorporates the concept and
principles of Bilateral Filters retaining the motion boundaries by taking into
account the difference both in value and distance in a manner very similar to
Gaussian convolution. The optical flow is obtained by applying the proposed
method at certain locations selected based on the present motion differences
and then performing non-uniform interpolation in a multi-scale iterative
framework. Experiments with several well-known datasets with and without
ground-truth show that our scheme outperforms recently proposed
state-of-the-art phase correlation based optical flow methods.
