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Fine-grained hand gesture recognition based on active acoustic signal for VR systems

journal contribution
posted on 09.08.2021, 06:58 by Wenhao Jiang, Si Li, Yanchao Zhao, Huawei TuHuawei Tu, Chengyong Liu
Hand gestures are the nature and dominant interaction interfaces for VR systems. The state of the art interaction mechanism for VR system either requires expensive sensing devices or suffers from accuracy issues thus hard to perform versatile interactions. In this paper, we leverage Ultragloves, a low cost interaction system using microphone-implanted gloves to extract the hand gestures. With specifically designed signals, we manage to get both the distance and the directions in a relatively accurate manner. We then design a CNN-LSTM like learning algorithm to extract the gestures. Furthermore, to improve the accuracy of recognition, we also design a filter algorithm to filter out noisy data. The implementation shows that our method can recognize four micro-gestures in the accuracy of 82% by combining phase and frequency features.

History

Publication Date

01/12/2020

Journal

CCF Transactions on Pervasive Computing and Interaction

Volume

2

Issue

4

Pagination

(p. 329-339)

Publisher

Springer Science and Business Media LLC

ISSN

2524-521X

Rights Statement

© China Computer Federation (CCF) 2020

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