Directional filters and a new structure for estimation of optical flow

Abstract

We study the use of directional filters with application to estimation of dense velocity fields. We suggest a new type of directional filters based on the discrete prolate spheroidal sequence (DPSS). These filters are used for two purposes, decomposition of images in subimages with directional information, and a set of quadrature filters based on the DPSS is used for estimation of direction. For efficient computation of optical flow we suggest a new structure using 2D directional filters. After a set of scale space filters the image sequence is decomposed in subsequences with directional properties. For each direction phase space-time slices is extracted and a set of directional quadrature filters is used to estimate component velocities. The component velocities are finally used for estimation of a full velocity field. Compared to other methods our system is among the best, when accuracy, density and computational complexity is considered.