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.