Temporal derivatives in compressed video sensing

In this paper we propose a method to incorporate the inter-frame correlation to the problem of compressed video sensing (CVS) by means of high-order accuracy differential approximations. In particular, we encode high-frequency motion dynamics between consecutive frames in order to recover video data from under-sampled scheme. The proposed methodology couples the problem of compressed video sampling with motion dynamics to provide a unique protocol for CVS recovery. Numerical evaluations validate the proposed method by tracking high-frequency components between consecutive frames in video and effectively enhancing the recovery performance compared to the conventional CVS methods.