Pedestrian detection algorithm based on Faster RCNN

Chen Yulin

Proceedings of the 6th EAI International Conference on IoT in Urban Space, Urb-IoT 2021, 20-21 December 2021, Shenzhen, People’s Republic of China

Research Article

Pedestrian detection algorithm based on Faster RCNN

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Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/eai.20-12-2021.2315018,
    author={Chen  Yulin},
    title={Pedestrian detection algorithm based on Faster RCNN},
    proceedings={Proceedings of the 6th EAI International Conference on IoT in Urban Space, Urb-IoT 2021, 20-21 December 2021, Shenzhen, People’s Republic of China},
    publisher={EAI},
    proceedings_a={EAI URB-IOT},
    year={2022},
    month={5},
    keywords={pedestrian detection deep learning faster rcnn},
    doi={10.4108/eai.20-12-2021.2315018}
}

Chen Yulin
Year: 2022
Pedestrian detection algorithm based on Faster RCNN
EAI URB-IOT
EAI
DOI: 10.4108/eai.20-12-2021.2315018

Chen Yulin¹^,*

1: Guangdong Provincial Key Laboratory of Optical Information Materials and Technology & Institute of Electronic Paper Displays, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, P. R. China

*Contact email: 452263754@qq.com

Abstract

Pedestrians are the most frequent targets in video surveillance and vehicle camera shooting, and the safety of pedestrians is the most concerned issue of social and public safety. In order to avoid accidents and traffic accidents caused by dense personnel, real-time detection of pedestrians on the street is particularly important. For pedestrian detection in various actual scenes, accuracy and real-time have always been the key indicators. Aiming at the difficulty of target detection in video, this paper adopts fast r-cnn algorithm for pedestrian detection, solves the problem of real-time pedestrian detection in video, and improves the accuracy of detection.

Keywords: pedestrian detection deep learning faster rcnn

Published: 2022-05-27
Publisher: EAI

: http://dx.doi.org/10.4108/eai.20-12-2021.2315018