The recently introduced compressed sensing (CS) theory can, potentially, simplify the acquisition process of resource-limited devices by taking advantage of signal sparsity. This paper proposes a perceptual-based compressed video sensing (CVS) strategy that benefits from the human visual perception properties. Two frameworks are proposed, namely, Intra-perc-CVS and Inter-perc-CVS. In both frameworks, an efficient perceptual-based weighting strategy is applied for acquisition and recovery. In the Intra-perc-CVS scheme, video frames are acquired and recovered separately, while in the Inter-perc-CVS scheme, the frames are recovered jointly to further exploit inter-frame correlation. The proposed perceptual-based frameworks show remarkable performance improvement over the standard CVS.