A　low-complexity　saliency　detection　algorithm　for　perceptual　video　coding　is　proposed;　low-level　encoding　information　is　adopted　as　the　characteristics　of　visual　perception　analysis.　Firstly,　this　algorithm　employs　motion　vector　(MV)　to　extract　temporal　saliency　region　through　fast　MV　noise　filtering　and　translational　MV　checking　procedure.　Secondly,　spatial　saliency　region　is　detected　based　on　optimal　prediction　mode　distributions　in　I-frame　and　P-frame.　Then,　it　combines　the　spatiotemporal　saliency　detection　results　to　define　the　video　region　of　interest　(VROI).　The　simulation　results　validate　that　the　proposed　algorithm　can　avoid　a　large　amount　of　computation　work　in　the　visual　perception　characteristics　analysis　processing　compared　with　other　existing　algorithms;　it　also　has　better　performance　in　saliency　detection　for　videos　and　can　realize　fast　saliency　detection.　It　can　be　used　as　a　part　of　the　video　standard　codec　at　medium-to-low　bit-rates　or　combined　with　other　algorithms　in　fast　video　coding.