Aerodynamic analysis via foreground segmentation

Abstract

Results from wind-tunnel testing of athletes cannot always be repeated on the track, but reducing aerodynamic drag is critical for racing. Drag force is highly correlated with an athlete's frontal area, so in this paper we describe a system to segment an athlete from the very challenging background found in a standard racing environment. Given an accurate segmentation, a front-on view, and the athlete's position (for scaling), one can effectively count the pixels and thereby measure the moving area. The method described does not rely on alteration of the track lighting, background, or athlete's appearance. An image-matting algorithm more used in the film industry is combined with an innovative model-based pre-process to allow the whole measurement to be automated. Area results have better than one percent error compared to handextracted measurements over a representative period, while frame-by-frame measurements capture expected cyclic variation. A near real-time implementation permits rapid iteration of aerodynamic experiments during training.