Global motion estimation in frequency and spatial domain

We propose a fast and robust global motion estimation (GME) algorithm, based on a 2-stage coarse-to-fine refinement strategy, which is capable of measuring large motions. A 6-parameter affine motion model has been used. Coarse estimation is carried out in the frequency domain using polar, log-polar or log-log sampling of the Fourier magnitude spectrum of the sub-sampled image. The sampling scheme is adaptively selected, based on past motion patterns. The refinement stage consists of a RANSAC based model fitting to motion vectors of randomly selected high-activity blocks, and hence is robust to outliers. The motion vector of blocks is measured using phase correlation, which offers two advantages in this context: sub-pixel accuracy without significant computational overhead; and if a particular block consists of background as well as foreground pixels, both motions are simultaneously measured. Due to its hardware-friendly nature, the proposed algorithm holds potential for real-time GME even for television images.