Where are you going? Using human locomotion models for target estimation

Abstract

To explore virtual environments that are larger than the available physical tracking space by real walking, it is necessary to use so-called redirected walking. Redirection techniques allow the user to explore an unlimited virtual environment in a limited tracking space by introducing a small mismatch between a user's real and virtual movement, thus preventing the user from colliding with the physical walls of the tracking space. Steering algorithms are used to select the most suitable redirection technique at any given time, depending on the geometry of the real and virtual environment. Together with prediction of a user's future walking path, these algorithms select the best redirection strategy by an optimal control scheme. In this paper, a new approach for the prediction of a person's locomotion target is presented. We use various models of human locomotion together with a set of possible targets to create a set of expected paths. These paths are then compared to the real path the user already traveled to calculate the probability of a certain target being the one the user is heading for. A new approach for comparing paths with each other is introduced and is compared to three others. For describing the human's path to a given target, four different models are used and compared. To gather data for the comparison of the models against the real path, a user study was conducted. Based on the results of the user study, the paper concludes with a discussion on the prediction performance of the different approaches.