Asymmetric Bilateral Phase Correlation for Optical Flow Estimation in the Frequency Domain

Abstract

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 multiscale 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.

Vision Tracking: A Survey of the State-of-the-Art

“…In phase-based techniques, the optical flow is calculated in the frequency domain by applying the local phase correlation to the frames [56]. Unlike energy-based methods, velocity is represented by the outputs of the filter exhibiting the phase behavior.…”