RealNav: Exploring natural user interfaces for locomotion in video games

We present a reality-based locomotion study directly applicable to video game interfaces; specifically, locomotion control of the quarterback in American football. Focusing on American football drives requirements and ecologically grounds the interface tasks of: running down the field, maneuvering in a small area, and evasive gestures such as spinning, jumping, and the ¿juke. The locomotion interface is constructed by exploring data interpretation methods on two commodity hardware configurations. The choices represent a comparison between hardware available to video game designers, trading off traditional 3D interface data for greater hardware availability. Configuration one matches traditional 3D interface data, with a commodity head tracker and leg accelerometers for running in place. Configuration two uses a spatially convenient device with a single accelerometer and infrared camera. Data interpretation methods on configuration two use two elementary approaches and a third hybrid approach, making use of the disparate and intermittent input data combined with a Kalman filter. Methods incorporating gyroscopic data are used to further improve the interpretation. Our results show spatially convenient hardware, currently in many gamers´ homes, when properly interpreted can lead to more robust interfaces. We support this by a user evaluation on the metrics of position and orientation accuracy, range and gesture recognition.