Infrared image recognition method for pedestrian and vehicles based on improved YOLO

Zheng Li; Hong-qiang Wang; Hui Xue; Shuo Zhang; Shi-qiang Wang

doi:10.1117/12.2587231

12 March 2021 Infrared image recognition method for pedestrian and vehicles based on improved YOLO

Zheng Li, Hong-qiang Wang, Hui Xue, Shuo Zhang, Shi-qiang Wang

Proceedings Volume 11763, Seventh Symposium on Novel Photoelectronic Detection Technology and Applications; 117635B (2021) https://doi.org/10.1117/12.2587231
Event: Seventh Symposium on Novel Photoelectronic Detection Technology and Application 2020, 2020, Kunming, China

Abstract

Aiming at the problems of low real-time and low accuracy in target recognition of pedestrians and vehicles in infrared images, as well as missing long-distance detection, a YOLO-based deep learning method for pedestrian and vehicle recognition was proposed. First, image preprocessing and data enhancement are applied to improve the generalization ability of the model; then the network structure were changed, as well as the multi-scale feature detection map and the PANet structure were applied to improve the recognition ability of different scale targets; finally the attention mechanism was applied to improve the detection accuracy. In the simulation, the actual collected infrared pedestrian and vehicle data sets were used for training, and got the training model. Then the proposed method was transplanted to the embedded GPU platform to verify the performance of the algorithm. The result shows that the recognition accuracy rate reaches 84.35%, 12.44% improved compared with the original YOLO method, and the speed has reached 88 frames per second, which can meet the actual engineering needs.

Citation Download Citation

Zheng Li, Hong-qiang Wang, Hui Xue, Shuo Zhang, and Shi-qiang Wang "Infrared image recognition method for pedestrian and vehicles based on improved YOLO", Proc. SPIE 11763, Seventh Symposium on Novel Photoelectronic Detection Technology and Applications, 117635B (12 March 2021); https://doi.org/10.1117/12.2587231

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