Study on Pedestrian Detection Method Based on HOG Features and SVM

被引：1
|
作者：
Xi Hai-yan [1 ]
Xiao Zhi-tao [1 ]
Zhang Fang [1 ]
机构：
[1] Tianjin Polytech Univ TJPU, Sch Informat & Commun Engn, Tianjin 300160, Peoples R China
来源：
COMPUTATIONAL MATERIALS SCIENCE, PTS 1-3 | 2011年 / 268-270卷
关键词：
pedestrian detection; histograms of oriented gradient features; support vector machine;
D O I：
10.4028/www.scientific.net/AMR.268-270.1786
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The research of pedestrian detection ahead of vehicle is the front direction in the field of vehicle safety assistant driving at present. The method of SVM pedestrian detection based on HOG features is studied in this paper. Firstly, the histograms of oriented gradient features between pedestrian and non-pedestrian samples are extracted. Then the features are used as an input vector of SVM algorithm, getting pedestrian classifier with a higher recognition by training. Finally the trained classifier is loaded into the online pedestrian detection system to detect the transport road image. The experimental results show that the algorithm can effectively identify the different scales and attitude pedestrian in complex background.
引用
收藏
页码：1786 / +
页数：2
相关论文
共 50 条
  • [1] Improved pedestrian detection algorithm based on HOG and SVM
    Tu, Renwei
    Zhu, Zhongjie
    Bai, Yongqiang
    Journal of Computers (Taiwan), 2020, 31 (04) : 211 - 221
  • [2] Research on pedestrian detection technology based on the SVM classifier trained by HOG and LTP features
    Zhou, Hongzhi
    Yu, Gan
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2021, 125 : 604 - 615
  • [3] Pedestrian detection based on the improved HOG features
    Meng, Jianliang
    Li, Shujin
    PROCEEDINGS OF THE 2015 2ND INTERNATIONAL WORKSHOP ON MATERIALS ENGINEERING AND COMPUTER SCIENCES (IWMECS 2015), 2015, 33 : 701 - 704
  • [4] A new pedestrian detection method based on combined HOG and LSS features
    Yao, Shihong
    Pan, Shaoming
    Wang, Tao
    Zheng, Chunhou
    Shen, Weiming
    Chong, Yanwen
    NEUROCOMPUTING, 2015, 151 : 1006 - 1014
  • [5] Pedestrian Detection Based on HOG Features and SVM Realizes Vehicle-Human Environment Interaction
    Ma Nan
    Chen Li
    Hu JianCheng
    Shang QiuNa
    Li JiaHong
    Zhang GuoPing
    2019 15TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS 2019), 2019, : 287 - 291
  • [6] Detection of Drowsiness based on HOG features and SVM classifiers
    Pauly, Leo
    Sankar, Deepa
    2015 IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN), 2015, : 181 - 186
  • [7] Research and Performance analysis on Pedestrian Detection based on Optimized Hog and SVM
    Zhang, Yanxi
    Feng, Kaiping
    SENSORS, MECHATRONICS AND AUTOMATION, 2014, 511-512 : 247 - 250
  • [8] Pedestrian detection based on HOG and weak-label structural SVM
    Zhou, Z. (zzp@jiangnan.edu.cn), 1600, Binary Information Press, P.O. Box 162, Bethel, CT 06801-0162, United States (10):
  • [9] Pedestrian Detection Using Boosted HOG Features
    Wang, Zhen-Rui
    Jia, Yu-Lan
    Huang, Hua
    Tang, Shu-Ming
    PROCEEDINGS OF THE 11TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, 2008, : 1155 - +
  • [10] A novel pedestrian detection method based on combination of LBP, HOG, and Haar-like features
    Abari, Mina Etehadi
    2018 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY (EIT), 2018, : 55 - +
12345