This paper proposes compressed video sensing system that efficiently exploits spatial
and temporal redundancies in video signal. Our system utilizes perceptual features of
human eyes to focus the measurements and recovery on the most pronounced visual
coefficients in video frames. Low complexity residual-based recovery is proposed to
exploit inter-frame correlation. Simulation results demonstrate the efficiency of our
proposed system both in quality and complexity.