UIST '19: Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology
AwardHonorable Mention Award

MeCap: Whole-Body Digitization for Low-Cost VR/AR Headsets

Karan Ahuja, Robert Xiao, Mayank Goel, Chris Harrison

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Abstract

Low-cost, smartphone-powered VR/AR headsets are becoming more popular. These basic devices – little more than plastic or cardboard shells – lack advanced features, such as controllers for the hands, limiting their interactive capability. Moreover, even high-end consumer headsets lack the ability to track the body and face. For this reason, interactive experiences like social VR are underdeveloped. We introduce MeCap, which enables commodity VR headsets to be augmented with powerful motion capture (“MoCap”) and user-sensing capabilities at very low cost (under $5). Using only a pair of hemi-spherical mirrors and the existing rear-facing camera of a smartphone, MeCap provides real-time estimates of a wearer’s 3D body pose, hand pose, facial expression, physical appearance and surrounding environment – capabilities which are either absent in contemporary VR/AR systems or which require specialized hardware and controllers. We evaluate the accuracy of each of our tracking features, the results of which show imminent feasibility.

Citation

Ahuja, K., Harrison, C., Goel, M., & Xiao, R. (2019, October). Mecap: Whole-body digitization for low-cost vr/ar headsets. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (pp. 453-462).

BibTeX

@inproceedings{ahuja2019mecap,
title={Mecap: Whole-body digitization for low-cost vr/ar headsets},
author={Ahuja, Karan and Harrison, Chris and Goel, Mayank and Xiao, Robert},
booktitle={Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology},
pages={453--462},
year={2019}
}