FBS_YOLO3 vehicle detection algorithm based on viewpoint information

Chunbao Huo; Zengwen Chen; Zhibo Tong; Ya Zheng

doi:10.1117/12.3014408

9 January 2024 FBS_YOLO3 vehicle detection algorithm based on viewpoint information

Chunbao Huo, Zengwen Chen, Zhibo Tong, Ya Zheng

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129690S (2024) https://doi.org/10.1117/12.3014408
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

The FBS_YOLO3 vehicle detection algorithm is a novel solution to the challenge of detecting vehicles in unstructured road scenarios with limited warning information. This algorithm builds upon the YOLOv3 model to deliver advanced multi-scale target detection. Firstly, FBS_YOLO3 incorporates four convolutional residual structures into the YOLOv3 backbone network to obtain deeper feature knowledge via down-sampling. Secondly, the feature fusion network is improved by implementing a PAN network structure which enhances the accuracy and robustness of viewpoint recognition through top-down and bottom-up feature fusion. Lastly, the K-means clustering fusion cross-comparison loss function is utilized to redefine the anchor frame by employing a K-means fusion cross-ratio loss function. This innovative approach solves the issue of mismatching the predetermined anchor frame size of the YOLOv3 network. Experimental results demonstrate that FBS_YOLO3 on a self-built dataset can improve mAP by 3.15% compared with the original network, while maintaining a quick detection rate of 37 fps. Moreover, FBS_YOLO3 can accurately detect vehicles, identify viewpoint information, and effectively solve the warning information insufficiency problem in unstructured road scenarios.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chunbao Huo, Zengwen Chen, Zhibo Tong, and Ya Zheng "FBS_YOLO3 vehicle detection algorithm based on viewpoint information", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129690S (9 January 2024); https://doi.org/10.1117/12.3014408

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