Depth　information　plays　an　important　role　in　the　human　visual　system.　Based　on　color　and　depth　features,　a　saliency　detection　model　was　proposed　in　this　paper　based　on　depth　selective　difference　and　prior　background　prior.　First,　the　proportion　of　color　and　depth　features　was　adjusted　according　to　the　quality　of　depth　map.　Second,　the　saliency　map　based　on　depth　selectivity　difference　was　calculated　according　to　the　intrinsic　characteristics　of　depth　map.Then,　based　on　the　acquired　boundary　background　set　and　depth　prior　background　set,　a　saliency　detection　method　was　presented　based　on　prior　background　prior.　Finally,　the　two　saliency　maps　obtained　in　the　previous　period　were　fused　and　adjusted,　and　the　saliency　maps　were　optimized　to　obtain　the　final　saliency　detection　result.　Experiments　on　two　publicly　available　datasets　show　that　the　proposed　method　performs　better　than　that　of　other　state-of-the-art　approaches.　©　2019,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.