Auto-recognition Pedestrians Research Based on HOG Feature and SVM Classifier for Vehicle Images

Yunsheng Li, Jie Cao, Xuewen Chen, Feng Zhao, Jingling Li
{"title":"Auto-recognition Pedestrians Research Based on HOG Feature and SVM Classifier for Vehicle Images","authors":"Yunsheng Li, Jie Cao, Xuewen Chen, Feng Zhao, Jingling Li","doi":"10.1109/RCAR49640.2020.9303268","DOIUrl":null,"url":null,"abstract":"In order to estimate the potential hazards and adopt strategies for preventing the accidents, this paper is about the research of auto-recognition pedestrians. Using the captured images of the vehicle recorder, based on the HOG feature processing technology and SVM classifier, the automatic detection and recognition of pedestrians are realized. In the past, the cost of pedestrian identification system is too high and its universality is poor. In this research, optimization methods of reasonable sample allocation and difficult training are used to make the training model more general and effective.","PeriodicalId":169202,"journal":{"name":"International Conference on Real-time Computing and Robotics","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Real-time Computing and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCAR49640.2020.9303268","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In order to estimate the potential hazards and adopt strategies for preventing the accidents, this paper is about the research of auto-recognition pedestrians. Using the captured images of the vehicle recorder, based on the HOG feature processing technology and SVM classifier, the automatic detection and recognition of pedestrians are realized. In the past, the cost of pedestrian identification system is too high and its universality is poor. In this research, optimization methods of reasonable sample allocation and difficult training are used to make the training model more general and effective.
基于HOG特征和SVM分类器的车辆图像行人自动识别研究
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信