Research on substation inspection behavior recognition algorithm based on human feature points

Xu Liu; Yubo Zhang; Lin Zou; Yufeng Lu; Chengwei Huang

doi:10.1117/12.3049685

8 November 2024 Research on substation inspection behavior recognition algorithm based on human feature points

Xu Liu, Yubo Zhang, Lin Zou, Yufeng Lu, Chengwei Huang

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134160V (2024) https://doi.org/10.1117/12.3049685
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

With the rapid development of computer vision and machine learning, behavior recognition technology has become a research hotspot and is widely used in video surveillance, human-computer interaction, virtual reality and other fields. Traditional behavior recognition methods mostly rely on complex pre-processing and manual feature extraction, which has high computational cost and poor robustness. In order to overcome these limitations, this paper proposes a new behavior recognition algorithm based on human feature points. Firstly, the deep learning technology is used to realize the real-time positioning and tracking of the key feature points of the human body through the open pose framework. This technology can accurately identify the 34 key points of the human body under various postures and lighting conditions. Secondly, based on these key point data, we build a lightweight convolutional neural network model to analyze the dynamics of human behavior and capture the spatio-temporal characteristics of behavior. Through training and testing on the public human3.6m data set, our model achieves 92% accuracy in behavior recognition, and can process 30 frames of video stream per second, showing excellent real-time performance. This research not only improves the efficiency and accuracy of behavior recognition, but also provides a valuable reference for future deployment in practical applications.

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

Citation Download Citation

Xu Liu, Yubo Zhang, Lin Zou, Yufeng Lu, and Chengwei Huang "Research on substation inspection behavior recognition algorithm based on human feature points", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134160V (8 November 2024); https://doi.org/10.1117/12.3049685

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Detection and tracking algorithms

Action recognition

Video

Education and training

Machine learning

Deep learning

Show All Keywords

Keywords/Phrases

Search In:

Publication Years