Existing　methods　in　RFID　systems　often　employ　presence　or　absence　fashion　to　detect　the　tags＇　motions,　so　they　cannot　meet　motion　detection　requirement　in　many　applications.　Our　recent　observations　suggest　that　the　signal　strength　backscattered　from　the　tag　is　hypersensitive　to　its　position,　inspiring　us　to　perceive　the　tag　motion　through　its　radio　signal　strength　changes.　Motion　perception　is　not　trivial　and　challenged　by　weak　stability　of　strength　in　that　any　other　interference　or　noise　may　incur　significant　changes　as　well,　resulting　in　high　false　positives.　To　tackle　this　issue,　we　propose　to　model　the　strength　via　the　Mixture　of　Gaussian　Model　(MoG).　The　problem　is　thus　converted　to　foreground　segment　in　computer　vision　with　the　help　of　Strength　Image,　where　the　technique　of　MoG　based　background　subtraction　is　employed.　We　then　implement　a　prototype　using　commercial　off-the-shelf　products.　The　evaluation　results　show　that　the　slightest　tag　motion　(similar　to　10cm)　can　be　precisely　perceived,　and　the　accuracy　is　up　to　9234%　while　the　false　positive　is　suppressed　under　0.5%.