David Pagnon PhD Defense 2023 #noparkour
Channel: David Pagnon
Date: 14/03/2023

Parkour videos are coming back soon! #noparkour

My PhD defense, presented on March 10th, 2023. 
Subtitles available in English.

"Design, evaluation, and application of a workflow for biomechanically consistent markerless kinematics in sports"
"Conception, évaluation, et application d'une méthode biomécaniquement cohérente de cinématique sans marqueurs en sport"

Manuscript, slides, and evaluation available there: https://github.com/davidpagnon/These_David_Pagnon
Questions in see this (unlisted) video: https://youtu.be/wVt-ZvjUKe0

Abstract:
Motion capture is traditionally performed with marker-based systems. However, these solutions are hardly compatible with on-field sports analysis, and markerless alternatives are being explored. One of the most promising prospects lies at the intersection of machine learning for 2D pose estimation, computer vision for 3D reconstruction from multiple video sources, and biomechanics for constraining 3D coordinates to an anatomically consistent model. We released Pose2Sim, an open-source package striving to answer these needs in a user-friendly way. OpenPose 2D keypoint coordinates are robustly triangulated, and serve as input for a full-body OpenSim inverse kinematics procedure. Pose2Sim robustness has been evaluated for people entering and exiting the field of view, degraded image quality, calibration errors, and decreased number of cameras. Its accuracy has also been assessed and deemed sufficient for walking, running, and cycling analysis. In the context of a competition, using lightweight action cameras can be convenient. We tested such hardware on boxing sequences and proposed post-calibration and post-synchronization procedures. Finally, capturing both the athlete and their equipment can be valuable. We explored the inverse kinematics of both a pilot and his bike in a BMX race by training a DeepLabCut bike model, triangulated and mapped on a custom-articulated OpenSim model. This work brings out interesting new perspectives for the analysis of sports movement.

00:00 Welcome
01:26 Introduction
15:08 From 2D images to 3D joint angles
26:22 Robustness
31:03 Accuracy
34:16 Application case
42:38 Perspectives
45:10 Conclusion