In this paper

a new kind of pedestrian detection method is investigated;the single DMP model is combined with the couple pedestrian DPM to solve the pedestrian detection problem because of the pedestrian visual occlusion under common traffic models.This method extracts DPM feature through dataset such as INRIA

ETH

and then obtains the single/couple DPM model through LatentSVM training method.Moreover

the traffic pedestrian.distribution scene can be classified and divided first and then separated and remixed by the classification detention method.Firstly the target image will match with couple pedestrian template SDP-DPM.Secondly if couple pedestrian target can not be detected

the scene will be classified as single distribution

and then matching template will switch to single pedestrian template

the results will be saved.Thirdly when the couple pedestrian are detected

the distribution will be classified and mixed

and then corresponding couple pedestrian filtering response can be saved.Finally the second matching will launch with single pedestrian template

weighted sum of the two detection results.The test proved that the method stated above can efficiently detect pedestrians under scenes that pedestrian heavily cover each other

and this method also can be more accurately compared with the traditional DPM method and other popular detection methods.