Virtually cloning real human with motion style

Abstract

Our goal is to capture style from real human motion so it can be rendered with a virtual agent that represents this human user. We used expressivity parameters to describe motion style. As a first contribution, we propose an approach to estimate a subset of expressivity parameters defined in the literature (namely spatial extent and temporal extent) from captured motion trajectories. Second, we capture the expressivity of real users and then output it to the Greta engine that animates a virtual agent representing the user. We experimentally demonstrate that expressivity can be another clue for identifiable virtual clones of real humans. © 2013 Springer-Verlag.