Journal of Guangxi Normal University(Natural Science Edition) ›› 2019, Vol. 37 ›› Issue (4): 61-67.doi: 10.16088/j.issn.1001-6600.2019.04.007

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Fast Pedestrian Detection Method Based on Multi-Features    and Implementation

XIAO Yiqun, SONG Shuxiang*, XIA Haiying   

  1. College of Electronic Engineering, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2018-09-06 Online:2019-10-25 Published:2019-11-28

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Abstract: Aimed at the pedestrian detection speed and related practical application problems, a fast multi-feature pedestrian detection method is proposed and applied to video monitoring system in this paper. Firstly, the Gaussian modeling is used to extract the effective motion region of the image, so that the detection area is reduced. Then, the extracted image is edge-processed, the HOG feature is merged with the LBP feature, and the classifier is trained using the support vector machine (SVM). Finally the pedestrian detection algorithm on the Hi3516A development board is conducted to monitor and detect in real time. Experiments are carried out on the PC side and the development board respectively. It is show that the method effectively improves the speed and achieves the real-time pedestrian detection requirements. The system runs stably and can be used in actual monitoring.

Key words: pedestrian detection, mixed Gaussian modeling, HOG, LBP, video surveillance

CLC Number: 

  • TP391.41
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