Object Based Optical Flow Estimation with an Affine Prior Model
Abstract
We investigate an original method to compute the optical flow on image sequences. Instead of assuming invariance principles applied to individual pixels, this method considers objects as a whole, by constraining their total intensity during their motion. A variational implementation of this method has already been studied. We propose here a parametric implementation of this method using an affine prior model. A combined method between the variational method and the affine method is proposed in order to capture both affine components and non-affine components. Results on meteorological infrared data are presented