Methodologies for the User Evaluation of the Motion of Virtual Humans

Virtual humans are employed in many interactive applications, including (serious) games. Their motion should be natural and allow interaction with its surroundings and other (virtual) humans in real time. Physical controllers offer physical realism and (physical) interaction with the environment. Because they typically act on a selected set of joints, it is hard to evaluate their naturalness in isolation. We propose to augment the motion steered by such a controller with motion capture, using a mixed paradigm animation that creates coherent full body motion. A user evaluation of this resulting motion assesses the naturalness of the controller. Methods from Signal Detection Theory provide us with evaluation metrics that can be compared among different test setups, observers and motions. We demonstrate our approach by evaluating the naturalness of a balance controller. We compare different test paradigms, assessing their efficiency and sensitivity.