WAVE: Anticipatory Movement Visualization for VR Dancing

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

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.

Citation

Laattala, M., Piitulainen, R., Ady, N. M., Tamariz, M., & Hämäläinen, P. (2024, May). WAVE: Anticipatory Movement Visualization for VR Dancing. Presented at CHI '24: CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA

• Presentation Conference Type: Conference Paper (published)
• Conference Name: CHI '24: CHI Conference on Human Factors in Computing Systems
• Start Date: May 11, 2024
• End Date: May 16, 2024
• Online Publication Date: May 11, 2024
• Publication Date: May 11, 2024
• Deposit Date: Oct 11, 2024
• Publicly Available Date: Oct 11, 2024
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Book Title: CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems
• ISBN: 979-8-4007-0330-0
• DOI: https://doi.org/10.1145/3613904.3642145