Pedestrian Detection Based on Gabor Feature Combined with Fast HOG Feature

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments

    Histogram of Oriented Gradients (HOG) feature extraction has a slow speed and is prone to the omission of detailed features in pedestrian detection. To tackle these problems, this study proposes a novel pedestrian detection algorithm based on Gabor feature combined with fast HOG feature. Specifically, the input image is first subjected to wavelet transform and the HOG feature of the image is quickly extracted using the idea of integral image and the principal component analysis algorithm. Then the fast HOG feature is fused with the Gabor feature obtained after Gabor wavelet transform. Finally, the hybrid features are used to train the classifier for effective pedestrian detection. The experimental results on the test set show that the detection accuracy of the hybrid feature extraction method is up to 7.37% higher than that of the single feature extraction method when the same classifier is used. Therefore, the proposed algorithm can effectively improve the accuracy of pedestrian detection.

    Cited by
Get Citation

任梦茹,侯宏录,韩修来. Gabor特征结合快速HOG特征的行人检测.计算机系统应用,2021,30(10):259-263

Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
  • Received:January 06,2021
  • Revised:February 03,2021
  • Adopted:
  • Online: October 08,2021
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a)
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063