RT journal article
T1 PyBodyTrack: A python library for multi-algorithm motion quantification and tracking in videos
A1 Ruiz Zafra, Ángel
A1 Pigueiras del Real, Janet
A1 Heredia-Jimenez, Jose
A1 Shah, Syed Taimoor Hussain
A1 Shah, Syed Adil Hussain
A2 Física de la Materia Condensada
A2 Ingeniería Informática
K1 Motion quantification
K1 Pose tracking
K1 Computer vision
K1 Human movement analysis
K1 Python library
AB Human movement analysis, driven by computer vision and pose tracking technologies, is gaining acceptancein healthcare, rehabilitation, sports, and daily activity monitoring. While most approaches focus on qualitativeanalysis (e.g., pattern recognition), objective motion quantification can provide valuable insights for diagnosis,progress tracking, and performance assessment. This paper introduces PyBodyTrack, a Python library for motionquantification using mathematical methods in real-time and pre-recorded videos. It simplifies video managementand integrates with position estimators like MediaPipe, YOLO, and OpenPose. PyBodyTrack enables seamlessmotion quantification through standardized metrics, facilitating its integration into various applications.
PB Elsevier
SN 2352-7110
YR 2025
FD 2025-07-11
LK http://hdl.handle.net/10498/37866
UL http://hdl.handle.net/10498/37866
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 14-nov-2026