To　investigate　the　different　modes　of　human　thinking,　we　designed　an　eye　tracking　experiment　during　people　recognized　two　category　images　of　histograms　and　scenes,　and　used　the　support　vector　machine　(SVM)　classification　algorithm　to　classify　these　eye　movement　data.　The　results　of　statistical　analysis　showed　that　there　were　significant　differences　in　saccade　distance　and　pupil　diameter　between　these　two　category　images.　By　the　feature　selection,　normalization　of　data　preprocessing,　and　SVM　classification,　the　results　of　classification　analysis　showed　that　there　was　a　better　performance　on　the　classification　of　the　histograms　and　scenes.　These　results　suggest　we　can　identify　the　modes　of　human　thinking　through　the　SVM　classification　methods　based　on　the　eye　movement　data.