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Found 4 papers, 2 papers with code
Machine Vision-Enabled Sports Performance Analysis
$\textbf{Goal:}$ This study investigates the feasibility of monocular 2D markerless motion capture (MMC) using a single smartphone to measure jump height, velocity, flight time, contact time, and range of motion (ROM) during motor tasks.
An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification
Additionally, a minimum of 3 IMUs are required to outperform a single camera.
Quantifying Jump Height Using Markerless Motion Capture with a Single Smartphone
This study evaluates how accurately markerless motion capture (MMC) with a single smartphone can measure bilateral and unilateral CMJ jump height.
Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series Classifiers
We analyze the accuracy and robustness of BodyMTS and show that it is robust to different types of noise caused by either video quality or pose estimation factors.
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