  In this paper, two simple principal component regression methods for
estimating the optical flow between frames of video sequences according to a
pel-recursive manner are introduced. These are easy alternatives to dealing
with mixtures of motion vectors in addition to the lack of prior information on
spatial-temporal statistics (although they are supposed to be normal in a local
sense). The 2D motion vector estimation approaches take into consideration
simple image properties and are used to harmonize regularized least square
estimates. Their main advantage is that no knowledge of the noise distribution
is necessary, although there is an underlying assumption of localized
smoothness. Preliminary experiments indicate that this approach provides robust
estimates of the optical flow.
