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BodyFlow: An Open-Source Library for Multimodal Human Activity Recognition.

Authors :
del-Hoyo-Alonso, Rafael
Hernández-Ruiz, Ana Caren
Marañes-Nueno, Carlos
López-Bosque, Irene
Aznar-Gimeno, Rocío
Salvo-Ibañez, Pilar
Pérez-Lázaro, Pablo
Abadía-Gallego, David
Rodrigálvarez-Chamarro, María de la Vega
Source :
Sensors (14248220). Oct2024, Vol. 24 Issue 20, p6729. 21p.
Publication Year :
2024

Abstract

Human activity recognition is a critical task for various applications across healthcare, sports, security, gaming, and other fields. This paper presents BodyFlow, a comprehensive library that seamlessly integrates human pose estimation and multiple-person estimation and tracking, along with activity recognition modules. BodyFlow enables users to effortlessly identify common activities and 2D/3D body joints from input sources such as videos, image sets, or webcams. Additionally, the library can simultaneously process inertial sensor data, offering users the flexibility to choose their preferred input, thus facilitating multimodal human activity recognition. BodyFlow incorporates state-of-the-art algorithms for 2D and 3D pose estimation and three distinct models for human activity recognition. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
20
Database :
Academic Search Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
180486323
Full Text :
https://doi.org/10.3390/s24206729