Compressive sensing in video applications

In this paper, a new approach to estimate motion parameters in compressive sensed video sequences is proposed. The proposed procedure combines sparse reconstruction algorithms and time-frequency analysis applied to μ-propagation signal. This concept allows providing precise velocity estimation even under a reduced number of randomly chosen video frames. The theory is applied and illustrated on synthetic and real video sequence.