Analysis of juggling data: Registering data to principal components to explain amplitude variation

Abstract

The paper considers an analysis of the juggling dataset based on registration. An elementary landmark registration is used to extract the juggling cycles from the data. The resulting cycles are then registered to functional principal components. After the registration step the paper then lays its focus on a functional principal component analysis to explain the amplitude variation of the cycles. More results about the behavior of the juggler’s movements of the hand during the juggling trials are obtained by a further investigation of the principal scores.