Research on recognition of dangerous driving behavior based on support vector machine

Liumei Zhang; Baoyu Tan; Tianshi Liu; Jiao Li

doi:10.1117/12.2589350

27 January 2021 Research on recognition of dangerous driving behavior based on support vector machine

Liumei Zhang, Baoyu Tan, Tianshi Liu, Jiao Li

Author Affiliations +

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117201L (2021) https://doi.org/10.1117/12.2589350
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

Research on dangerous driving behavior recognition is beneficial to regulate the driving behavior of drivers. As the existing algorithms are sensitive to noise, and abnormal data often affects the process of identifying dangerous driving behaviors. This paper proposes a novel driving behavior research method. Such method establishes a driving behavior recognition model based on Support Vector Machine (SVM) and oversampling. The experimental results show that the proposed model demonstrates a higher recognition rate.

Citation Download Citation

Liumei Zhang, Baoyu Tan, Tianshi Liu, and Jiao Li "Research on recognition of dangerous driving behavior based on support vector machine", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117201L (27 January 2021); https://doi.org/10.1117/12.2589350

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