文献类型：会议论文

英文题名：Pedestrian Detection Based on HOG Features and SVM Realizes Vehicle-Human Environment Interaction

作者：Ma Nan[1];Chen Li[1];Hu JianCheng[2];Shang QiuNa[2];Li JiaHong[1];Zhang GuoPing[1]

第一作者：马楠

通讯作者：Ma, N[1]

机构：[1]Beijing Union Univ, Software Engn, Coll Robot, Beijing Key Lab Informat Serv Engn, Beijing, Peoples R China;[2]Beijing Union Univ, Software Engn, Coll Robot, Beijing, Peoples R China

第一机构：北京联合大学北京市信息服务工程重点实验室|北京联合大学机器人学院

通讯机构：[1]corresponding author), Beijing Union Univ, Software Engn, Coll Robot, Beijing Key Lab Informat Serv Engn, Beijing, Peoples R China.|[1141739]北京联合大学机器人学院;[11417]北京联合大学;[11417103]北京联合大学北京市信息服务工程重点实验室;

会议论文集：15th International Conference on Computational Intelligence and Security (CIS)

会议日期：DEC 13-16, 2019

会议地点：Macao, PEOPLES R CHINA

语种：英文

外文关键词：HOG; SVM; pedestrian detection; visualization

摘要：Autonomous driving has to deal with human-vehicle interaction, in which one of the key tasks is to detect pedestrians. In this paper, HOG, a classical algorithm in the pedestrian detection field is used for extracting features and SVM for pedestrian classifier training. The pedestrian feature classifier is obtained through training and testing using INRIA pedestrian dataset and data acquired by autonomous vehicles. Meanwhile, we design a pedestrian detection visualization system for better application on autonomous vehicles to detecting pedestrian. This system detects the image data input by users and calls the pedestrian feature classifier that has been trained to effectively mark pedestrians.