Perceiving human motion variety

In order to simulate plausible groups or crowds of virtual characters, it is important to ensure that the individuals in a crowd do not look, move, behave or sound identical to each other. Such obvious 'cloning' can be disconcerting and reduce the engagement of the viewer with an animated movie, virtual environment or game. In this paper, we focus in particular on the problem of motion cloning, i. e., where the motion from one person is used to animate more than one virtual character model. Using our database of motions captured from 83 actors (45M and 38F), we present an experimental framework for evaluating human motion, which allows both the static (e.g., skeletal structure) and dynamic aspects (e.g., walking style) of an animation to be controlled. This framework enables the creation of crowd scenarios using captured human motions, thereby generating simulations similar to those found in commercial games and movies, while allowing full control over the parameters that affect the perceived variety of the individual motions in a crowd. We use the framework to perform an experiment on the perception of characteristic walking motions in a crowd, and conclude that the minimum number of individual motions needed for a crowd to look varied could be as low as three. While the focus of this paper was on the dynamic aspects of animation, our framework is general enough to be used to explore a much wider range of factors that affect the perception of characteristic human motion.