Research on Pedestrian Intelligent Recognition Method Based on Cascade Classifier Structure

Abstract

In order to classify pedestrians from the mixed multi-objective traffic scene quickly and accurately, this paper proposes an intelligent pedestrian recognition method based on the cascade classifier structure. Using the “from coarse to fine” strategy, a double-layer hierarchical series combination classifier is designed. HGA-BP classifier with two-layer structure is used for pedestrian recognition. Firstly, the candidates are extracted by combining the basic characteristics of the target object shape, in order to quickly eliminate most of the non-target areas, and then use the advanced features of the target to identify the candidate target areas after the processing of the previous classifier. Through the experimental analysis, this method can better classify and identify pedestrians and other negative moving objects, and count the number of pedestrians in the whole traffic scene accurately.