Efficient　motion　detection　is　essential　for　the　Internet　of　Things.　However,　it　suffers　from　overloading　redundant　static　background　information.　Inspired　by　the　human　visual　system,　which　is　efficient　in　motion　detection,　we　propose　a　silicon-based　retinomorphic　photodetector　with　a　simple　metal/insulator/semiconductor　(MIS)　structure,　which　is　compatible　with　the　complementary　metal-oxide-semiconductor　(CMOS)　industry.　In　contrast　to　conventional　photodetectors　that　generate　a　sustained　photocurrent,　our　retinomorphic　photodetector　is　sensitive　only　to　the　change　in　light　intensity　and　therefore　filters　the　redundant　static　background.　In　addition,　it　shows　logarithmic　dependence　on　the　light　intensity,　which　simplifies　the　contrast　ratio　measurement.　Based　on　our　moving　object　recognition　experiment,　after　filtering　background　information,　the　information　to　be　analyzed　is　reduced　to　27.3%,　thereby　improving　the　image　recognition　efficiency　in　the　subsequent　processing　tasks.　This　innovative　and　industry-compatible　retinomorphic　photodetector　will　facilitate　the　construction　of　future　efficient　motion　detection　systems.