Robust skeletal motion tracking using temporal and spatial synchronization of two video streams.

ABSTRACT: Accurate and reliable skeletal motion tracking is essential for rehabilitation monitoring, enabling objective assessment of patient progress and facilitating telerehabilitation applications. Traditional marker-based motion capture systems, while highly accurate, are costly and impractical for home rehabilitation, whereas marker-less methods often suffer from depth estimation errors and occlusions. Recent studies have explored various computer vision and deep learning approaches for human pose estimation, yet challenges remain in ensuring robust depth accuracy and tracking under occlusion conditions. This study proposes a three-dimensional human skeleton tracking system for upper limb activities that integrates temporal and spatial synchronization to improve depth estimation accuracy for re

SUBMITTER: Abromavicius V 

PROVIDER: S-EPMC12331063 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature