WAVE: Anticipatory Movement Visualization for VR Dancing

Markus Laatala, Roosa Piitulainen, Nadia M. Ady, Monica Tamariz, Perttu Hämäläinen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Dance games are one of the most popular game genres in Virtual Reality (VR), and active dance communities have emerged on social VR platforms such as VR Chat. However, effective instruction of dancing in VR or through other computerized means remains an unsolved human-computer interaction problem. Existing approaches either only instruct movements partially, abstracting away nuances, or require learning and memorizing symbolic notation. In contrast, we investigate how realistic, full-body movements designed by a professional choreographer can be instructed on the fly, without prior learning or memorization. Towards this end, we describe the design and evaluation of WAVE, a novel anticipatory movement visualization technique where the user joins a group of dancers performing the choreography with different time offsets, similar to spectators making waves in sports events. In our user study (N=36), the participants more accurately followed a choreography using WAVE, compared to following a single model dancer.
Original languageEnglish
Title of host publicationCHI PLAY 2023
Subtitle of host publicationAnnual Symposium on Computer-Human Interaction in Play
PublisherAssociation for Computing Machinery
Publication statusAccepted/In press - 24 Jan 2024

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