A Perceptual Model-Based Approach to Plausible Authoring of Vibration for the Haptic Metaverse

Abstract

Haptic virtual reality is often misunderstood as being solely a physically identical copy of real environments. Thus, a perfect recording and reproduction of vibration that is indistinguishable in an A:B comparison is often the aim. However, in most virtual reality applications the real environment is not available for direct comparison. Instead, when judging the plausibility of a presented scene, the user compares the vibration to his expectations shaped by the audiovisual context. Therefore, it should be sufficient to find any vibration that the user expects to potentially occur in the given context. Such a vibration needs to elicit a perceptual profile with a minimal distance to an expected profile in the sensory tactile perceptual space. Building onto this formalization, this article demonstrates a novel generative model-based approach to authoring vibrations. First, users quantify expectations as tactile profiles consisting of ratings of six sensory tactile attributes without the presence of vibrations. Subsequently, the model predicts vibration parameters from such profiles. This ensures the fulfillment of user expectations and thus high plausibility. Furthermore, it eliminates the necessity of recordings, infeasible for scenes with no real counterpart and opens the door to crowdsourcing the authoring process with laypersons for the haptic metaverse.