Research on human activity classification based on K-nearest algorithm model

Weilan Qi; Hanyi Yao; Haolin Song

doi:10.1117/12.2679236

25 May 2023 Research on human activity classification based on K-nearest algorithm model

Weilan Qi, Hanyi Yao, Haolin Song

Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 127120E (2023) https://doi.org/10.1117/12.2679236
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China

Abstract

The classification of human activities plays an important role in sports, medical care and other fields. This paper is based on the measurement data of the nine-axis sensorfirstly, the time domain characteristics of sensor data are extracted, and the dimension of the data is reduced by principal component analysis. By comparison, a K- nearest neighbor algorithm classification model is designed and optimized for human activity classification.

Citation Download Citation

Weilan Qi, Hanyi Yao, and Haolin Song "Research on human activity classification based on K-nearest algorithm model", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 127120E (25 May 2023); https://doi.org/10.1117/12.2679236

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