In this paper a video-based method to automatically track instantaneous velocities of a swimmer is presented. Single cameras were used to follow a marker (LED) attached to the body. The method is inspired by particle tracking techniques, traditionally used in the field of fluid dynamics, to measure local velocities of a fluid flow. During the validation experiment, a white LED was attached to the hip of a swimmer together with a speedometer. A swimmer performed four different stroke types. The velocity profiles using LED tracking were captured and showed less noise than the speedometer measurements. Only at times when the marker disappeared above the water surface due to body role in front crawl and backstroke swimming did the LED tracking fail to capture the athlete’s motion. The algorithm was tested in a 2D case with a single LED to illustrate the proof of principle, but should be suitable for implementation in a 3D analysis or multiple LED analysis.@en

Abstract: We discuss the application of synthetic aperture particle image velocimetry for measuring the flow around human swimmers using small bubbles as tracer. We quantify the two-dimensional projection of the velocity field in planes perpendicular to the viewing direction of an array of six cameras. With help of simulations, modelled after the experiment, we address questions about depth selectivity and occlusion in dense bubble fields. Using vortex rings in the swimming pool, we provide a proof of principle of the method. It is further illustrated by the vorticity field produced by a human swimmer. Graphic abstract: [Figure not available: see fulltext.].@en