In　this　paper,　we　propose　a　novel　compressive　sensing　depth　video　(CSDV)　coding　scheme　based　on　Gaussian　mixture　models　(GMM)　and　object　edges.　We　first　compress　several　depth　videos　to　get　CSDV　frames　in　the　temporal　direction.　A　whole　CSDV　frame　is　divided　into　a　set　of　non-overlap　patches　in　which　object　edges　is　detected　by　Canny　operator　to　reduce　the　computational　complexity　of　quantization.　Then,　we　allocate　variable　bits　for　different　patches　based　on　the　percentages　of　non-zero　pixels　in　every　patch.　The　GMM　is　used　to　model　the　CSDV　frame　patches　and　design　product　vector　quantizers　to　quantize　CSDV　frames.　The　experimental　results　show　that　our　compression　scheme　achieves　a　significant　Bjontegaard　Delta　(BD)-PSNR　improvement　about　2–10　dB　when　compared　to　the　standard　video　coding　schemes,　e.g.　Uniform　Scalar　Quantization-Differential　Pulse　Code　Modulation　(USQ-DPCM)　and　H.265/HEVC.　©　Springer　International　Publishing　AG,　part　of　Springer　Nature　2018.