Intelligent motion monitoring system based on multisource feature fusion

Haorui Wen

doi:10.1117/12.3050012

11 December 2024 Intelligent motion monitoring system based on multisource feature fusion

Haorui Wen

Author Affiliations +

Proceedings Volume 13441, International Conference on Cloud Computing and Communication Engineering (CCCE 2024); 134410J (2024) https://doi.org/10.1117/12.3050012
Event: International Conference on Cloud Computing and Communication Engineering (CCCE 2024), 2024, Nanjing, China

Abstract

Incorrect motion state detection is a significant obstacle of motion monitoring systems in application of the real world. To address this issue, this paper proposes a multi-source feature fusion-based intelligent motion monitoring (IMM) system. First, an edge-end (EE) motion monitoring module is designed to recognize physical movements. The EE module adopts MoveNet model to detect pose keypoints in video frames, then the extracted keypoint coordinate information is classified to the EE motion features. Second, a Kalman fusion filtering (KFF) algorithm is designed for the to extract device-end (DE) module features. The KFF algorithm combines acceleration and angular velocity features to acquire the accurate inertial features of the device-end module, which effectively mitigating external interference caused by device movement. Based on these, the IMM system is built based on the wireless communication between the EE module and the DE module. Then, the IMM system integrates multi-source features from computer vision and inertial sensors, realizing the real-time monitoring of physical movements. The experimental results validate the IMM system for real-time movement monitoring in real-world scenarios.

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

Citation Download Citation

Haorui Wen "Intelligent motion monitoring system based on multisource feature fusion", Proc. SPIE 13441, International Conference on Cloud Computing and Communication Engineering (CCCE 2024), 134410J (11 December 2024); https://doi.org/10.1117/12.3050012

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
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Feature extraction

Feature fusion

Intelligence systems

Algorithm development

Motion models

Sensors

Detection and tracking algorithms

Show All Keywords

Keywords/Phrases

Search In:

Publication Years