From Athlete to Algorithm

The presentation demonstrates computer vision and artificial intelligence applied to Olympic canoe athlete training videos.
The system uses foreground-background separation to detect canoes and identify the waterline, then employs pose detection to locate paddle positions. Marc Schuh’s approach trains neural networks to recognize critical paddle positions during routine training.
Biomechanical refinements enhance accuracy in analysis. The solution dramatically accelerates what traditionally required manual frame-by-frame video screening—reducing a 20-minute per-athlete analysis to substantially less time.
Dr. Schuh brings unique expertise as a former Paralympic wheelchair sprinter who competed across three Games, achieving world championship status and European records.