Velocity estimation from images sequence and application to super-resolution

We present a method for approximating optical flow (velocity field) by a scaled piece-wise regular vector field. The method can be formulated in a variational manner that has a strong analogy to the Mumford and Shah (1985) functional for segmenting gray level image and in particular to the region merging minimization procedure described by Morel and Soluminini (1995). The proposed functional balances a complexity term (which can be the usual sum of the boundary length) to the “ability” of pixels to move together (that is with the same model of velocity regardless of what it is). A key point that allows the method to overcome, to some extent, the non-uniqueness of the optical flow is that the segmentation is performed without any attribution of velocities to pixels or regions. Finally, we show that the obtained velocity field is, in some cases, accurate enough to perform a “Frame-Fusion” process. We show some applications of this “super-resolution” for law enforcement