Abstract Virtual Reality (VR) has increasingly attracted the attention of the computer animation community in search of more intuitive and effective alternatives to the current sophisticated user interfaces. Previous works in the literature already demonstrated the higher affordances offered by VR interaction, as well as the enhanced spatial understanding that arises thanks to the strong sense of immersion guaranteed by virtual environments. These factors have the potential to improve the animators’ job, which is tremendously skill-intensive and time-consuming. The present paper explores the opportunities provided by VR-based interfaces for the generation of 3D animations via armature deformation. To the best of the authors’ knowledge, for the first time a tool is presented which allows users to manage a complete pipeline supporting the above animation method, by letting them execute key tasks such as rigging, skinning and posing within a well-known animation suite using a customizable interface. Moreover, it is the first work to validate, in both objective and subjective terms, character animation performance in the above tasks and under realistic work conditions involving different user categories. In our experiments, task completion time was reduced by 26%, on average, while maintaining almost the same levels of accuracy and precision for both novice and experienced users.

Abstract Virtual character animation is receiving an ever-growing attention by researchers, who proposed already many tools with the aim to improve the effectiveness of the production process. In particular, significant efforts are devoted to create animation systems suited also to non-skilled users, in order to let them benefit from a powerful communication instrument that can improve information sharing in many contexts like product design, education, marketing, etc. Apart from methods based on the traditional Windows-Icons-Menus-Pointer (WIMP) paradigms, solutions devised so far leverage approaches based on motion capture/retargeting (the so-called performance-based approaches), on non-conventional interfaces (voice inputs, sketches, tangible props, etc.), or on natural language processing (NLP) over text descriptions (e.g., to automatically trigger actions from a library). Each approach has its drawbacks, though. Performance-based methods are difficult to use for creating non-ordinary movements (flips, handstands, etc.); natural interfaces are often used for rough posing, but results need to be later refined; automatic techniques still produce poorly realistic animations. To deal with the above limitations, we propose a multimodal animation system that combines performance- and NLP-based methods. The system recognizes natural commands (gestures, voice inputs) issued by the performer, extracts scene data from a text description and creates live animations in which pre-recorded character actions can be blended with performer’s motion to increase naturalness.