A low cost visual hull based markerless system for the optimization of athletic techniques in outdoor environments

We propose a low cost 3D markerless motion analysis system for the optimization of athletic performance during training sessions. The system utilizes eight calibrated and synchronized High Definition (HD) cameras in order to capture a video of an athlete from different viewpoints. An improved kernel density estimation (KDE) based background segmentation algorithm is proposed to segment the athlete’s silhouettes from their background in each video frame. The silhouettes are then reprojected to reconstruct the 3D visual hull (VH) of the athlete. The center of the VH as an approximate representation of the body center of mass is then tracked over a number of frames. A set of motion analysis parameters are finally estimated and compared to the ones obtained by an outdoor state of the art marker-based system (Vicon). The proposed system is aimed at sports such as javelin, pole vault, and long jump and was able to provide comparable results with the Vicon system.