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A stretch-sensing soft glove for interactive hand pose estimation

Published: 28 July 2019 Publication History

Abstract

We present a stretch-sensing soft glove to interactively capture full hand poses with high accuracy and without requiring an external optical setup. Our device can be fabricated with simple tools available in most fabrication labs. The pose is reconstructed from a capacitive sensor array embedded in the glove. We propose a data representation that allows deep neural networks to exploit the spatial layout of the sensor itself. The network is trained only once, using an inexpensive off-the-shelf hand pose reconstruction system to gather the training data. The per-user calibration is then performed on-the-fly using only the glove.

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References

[1]
2019. CyberGlove. http://www.cyberglovesystems.com/.
[2]
2019. ManusVR glove. https://manus-vr.odoo.com/hardware.
[3]
Jean-Baptiste Chossat, Yiwei Tao, Vincent Duchaine, and Yong-Lae Park. 2015. Wearable soft artificial skin for hand motion detection with embedded microfluidic strain sensing. In Proc. ICRA. IEEE, 2568--2573.
[4]
Oliver Glauser, Daniele Panozzo, Otmar Hilliges, and Olga Sorkine-Hornung. 2019. Deformation Capture via Self-Sensing Capacitive Arrays. ACM Trans. Graph. 38, 2 (2019).
[5]
Anastasia Tkach, Andrea Tagliasacchi, Edoardo Remelli, Mark Pauly, and Andrew Fitzgibbon. 2017. Online Generative Model Personalization for Hand Tracking. ACM Trans. Graph. 36, 6 (2017).

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cover image ACM Conferences
SIGGRAPH '19: ACM SIGGRAPH 2019 Emerging Technologies
July 2019
54 pages
ISBN:9781450363082
DOI:10.1145/3305367
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2019

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Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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  • (2020)Ring-based finger tracking using capacitive sensors and long short-term memoryProceedings of the 25th International Conference on Intelligent User Interfaces10.1145/3377325.3377535(551-555)Online publication date: 17-Mar-2020

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