Cool Moves: User Motion Accentuation in Virtual Reality
Karan Ahuja, Eyal Ofek, Mar Gonzalez-Franco, Christian Holz, Andrew Wilson
Abstract
Current Virtual Reality (VR) systems are bereft of stylization and embellishment of the user's motion - concepts that have been well explored in animations for games and movies. We present CooIMoves, a system for expressive and accentuated full-body motion synthesis of a user's virtual avatar in real-time, from the limited input cues afforded by current consumer-grade VR systems, specifically headset and hand positions. We make use of existing motion capture databases as a template motion repository to draw from. We match similar spatio-temporal motions present in the database and then interpolate between them using a weighted distance metric. Joint prediction probability is then used to temporally smooth the synthesized motion, using human motion dynamics as a prior. This allows our system to work well even with very sparse motion databases (e.g., with only 3-5 motions per action). We validate our system with four experiments: a technical evaluation of our quantitative pose reconstruction and three additional user studies to evaluate the motion quality, embodiment and agency.
Citation
Ahuja, K., Ofek, E., Gonzalez-Franco, M., Holz, C., & Wilson, A. D. (2021). Coolmoves: User motion accentuation in virtual reality. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 5(2), 1-23.
BibTeX
@article{ahuja2021coolmoves,
title={Coolmoves: User motion accentuation in virtual reality},
author={Ahuja, Karan and Ofek, Eyal and Gonzalez-Franco, Mar and Holz, Christian and Wilson, Andrew D},
journal={Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies},
volume={5},
number={2},
pages={1--23},
year={2021},
publisher={ACM New York, NY, USA}
}