Smoothing techniques for 3D animated human pose estimation data
Virtual 3D reconstructions of live sport events are on the horizon and to produce a high quality experience for viewers it is important that the movements of the 3D models look natural. Today, state of the art pose estimators produce data that con-tains noise, resulting in jittery animations with pose errors. The goals for this thesis were to evaluate the performance of a Long Short-Term Memory (L
