25/04/2020

Touché: Data-Driven Interactive Sword Fighting in Virtual Reality

Javier Dehesa, Andrew Vidler, Christof Lutteroth, Julian Padget

Keywords: virtual reality, sword fighting, machine learning, animation, gesture recognition

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Abstract: VR games offer new freedom for players to interact naturally using motion. This makes it harder to design games that react to player motions convincingly. We present a framework for VR sword fighting experiences against a virtual character that simplifies the necessary technical work to achieve a convincing simulation. The framework facilitates VR design by abstracting from difficult details on the lower "physical" level of interaction, using data-driven models to automate both the identification of user actions and the synthesis of character animations. Designers are able to specify the character’s behaviour on a higher "semantic" level using parameterised building blocks, which allow for control over the experience while minimising manual development work. We conducted a technical evaluation, a questionnaire study and an interactive user study. Our results suggest that the framework produces more realistic and engaging interactions than simple hand-crafted interaction logic, while supporting a controllable and understandable behaviour design.

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