Publication Type

Conference Proceeding Article

Publication Date

6-2016

Abstract

This work presents Sonicnect, an acoustic sensing system with smartphone that enables accurate hands-free gesture input. Sonicnect leverages the embedded microphone in the smartphone to capture the subtle audio signals generated with fingers touching on the table. It supports 9 commonly used gestures (click, flip, scroll and zoom, etc) with above 92% recognition accuracy, and the minimum gesture movement could be 2cm. Distinguishable features are then extracted by exploiting spatio-temporal and frequency properties of the subtle audio signals. We conduct extensive real environment experiments to evaluate its performance. The results validate the effectiveness and robustness of Sonicnect.

Keywords

Acoustic sensing, Audio signal, Gesture input, Hands-free, Recognition accuracy, Spatio temporal

Discipline

Computer Sciences | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

MobiSys '16: Companion Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services: Singapore, Singapore, June 25-30, 2016

First Page

91

Last Page

91

ISBN

9781450344166

Identifier

10.1145/2938559.2948830

Publisher

ACM

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1145/2938559.2948830

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