An Immersive Annotation Tool for Movement Quality Assessment with 3D Visualization

Assessing human movement quality is essential in healthcare for diagnosing and monitoring musculoskeletal disorders. Traditional annotation methods are time-consuming and provide limited insights. In this work we present a web-based annotation tool tailored for efficient expert annotation of human exercises, featuring dual-angle RGB video views coupled with interactive 3D visualization of the movement and patient data integration. Through the concurrent streaming of 2D and 3D visualizations of a movement, the platform aims to streamline dataset creation, enhance annotation precision, and support the development of machine-learning based, Functional Capacity Evaluation (FCE) and rehabilitation systems.