Improved foggy pedestrian detection algorithm based on YOLOv5s

XiaoNing Feng; WenRong Jiang

doi:10.1117/12.2667416

22 February 2023 Improved foggy pedestrian detection algorithm based on YOLOv5s

XiaoNing Feng, WenRong Jiang

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 125871M (2023) https://doi.org/10.1117/12.2667416
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

To address the problem of low detection accuracy of YOLOv5s target detection algorithm in foggy traffic environment, an improved YOLOv5s-based pedestrian detection algorithm for foggy skies is proposed. The algorithm uses image defogging techniques to preprocess the data, expands the sample size by manually generating the Foggy Cityscapes-Person dataset through a new fog simulation pipeline algorithm, and enhances the network's ability to sense small targets under foggy skies by adjusting the loss function and the training method to improve the detection accuracy of pedestrians under foggy skies, resulting in an increase of the mAP value from 64.97% to The mAP value increases from 64.97% to 81.29%. The experimental results show that the YOLOv5s-ACE network model proposed in this paper effectively reduces the missing detection rate and false detection rate, and the model can quickly and accurately detect pedestrian targets in foggy sky scenes.

Citation Download Citation

XiaoNing Feng and WenRong Jiang "Improved foggy pedestrian detection algorithm based on YOLOv5s", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 125871M (22 February 2023); https://doi.org/10.1117/12.2667416

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available