4 citations · 5 across the 5 of their papers we have counts for
5 papers
Advancing Monocular Video-Based Gait Analysis Using Motion Imitation with Physics-Based Simulation
Nikolaos Smyrnakis, Tasos Karakostas, R. James Cotton
Gait analysis from videos obtained from a smartphone would open up many clinical opportunities for detecting and quantifying gait impairments. However, existing approaches for esti…
Self-Supervised Learning of Gait-Based Biomarkers
R. James Cotton, J. D. Peiffer, Kunal Shah +5
Markerless motion capture (MMC) is revolutionizing gait analysis in clinical settings by making it more accessible, raising the question of how to extract the most clinically meani…
Markerless Motion Capture and Biomechanical Analysis Pipeline
R. James Cotton, Allison DeLillo, Anthony Cimorelli +5
Markerless motion capture using computer vision and human pose estimation (HPE) has the potential to expand access to precise movement analysis. This could greatly benefit rehabili…
Improved Trajectory Reconstruction for Markerless Pose Estimation
R. James Cotton, Anthony Cimorelli, Kunal Shah +3
Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, inc…
Transforming Gait: Video-Based Spatiotemporal Gait Analysis
R. James Cotton, Emoonah McClerklin, Anthony Cimorelli +2
Human pose estimation from monocular video is a rapidly advancing field that offers great promise to human movement science and rehabilitation. This potential is tempered by the sm…