Dr. Marc Schuh is a Principal Consultant at TNG Technology Consulting in Munich. He specializes in software and enterprise architecture, where Conway’s Law frequently comes into play and reveals that many technical problems are, at their core, organizational challenges. His approach focuses on driving steady improvement through intrinsic motivation and pragmatic solutions.
Marc served as one of the tech leads in building Europe’s largest commercial data lake, migrated a legacy Visual Basic application to C# using the Strangler Pattern, and supports large enterprises in improving complex marketing data pipelines. Beyond his consulting work, he contributes to innovative prototypes — including automated performance analytics for Germany’s national canoeing team and experiments with brain–computer interfaces.
In his spare time, he maintains open-source projects promoting digital independence from major cloud providers (github.com/MarcSchuh). Before joining TNG, Marc earned a PhD in physics and competed as a 400 m wheelchair sprinter at three Paralympic Games, becoming a world champion and European record holder.
We introduce an innovative application of computer vision and artificial intelligence to analyze training videos of canoe athletes preparing for the Olympic Games. Our method employs foreground-background separation for canoe detection and waterline derivation. Through pose detection, we identify the paddle and have trained a neural network to recognize essential paddle positions for routine training analysis. Additionally, we incorporate biomechanical insights in a post-processing step to refine AI results and enhance analysis accuracy. Traditionally, biomechanics engineers manually screen training videos frame by frame to locate specific paddle positions and measure the paddle's angle relative to the waterline; a process taking about 20 minutes per athlete. Our approach significantly streamlines this process, reducing the workload by an order of magnitude.
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