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CapTap - Combining capacitive gesture recognition and acoustic touch detection

 
: Braun, Andreas; Zander-Walz, Sebastian; Krepp, Stefan; Rus, Silvia; Wichert, Reiner; Kuijper, Arjan

:

Matthies, Denys J.C. (Ed.); Haescher, Marian (Ed.); Bieber, Gerald (Ed.); Urban, Bodo (Ed.) ; Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Computer and Human Interaction -SIGCHI-:
iWOAR 2016, 3rd international Workshop on Sensor-based Activity Recognition and Interaction. Proceedings : June 23 - 24, 2016, Fraunhofer IGD, Univerity of Rostock
New York: ACM Press, 2016 (ACM International Conference Proceedings Series 1183)
ISBN: 978-1-4503-4245-2
Art. 6, 6 pp.
International Workshop on Sensor-based Activity Recognition (iWOAR) <3, 2016, Rostock>
English
Conference Paper
Fraunhofer IGD ()
capacitive sensor; capacitive proximity sensing; gesture recognition; Guiding Theme: Digitized Work; Research Area: Human computer interaction (HCI)

Abstract
Capacitive sensing is a common technology for finger-controlled touch screens. The variety of proximity sensors extends the range, thus supporting mid-air gesture interaction and application below any non-conductive materials. However, this comes at the cost of limited resolution for touch detection. In this paper, we present CapTap, which uses capacitive proximity and acoustic sensing to create an interactive surface that combines mid-air and touch gestures, while being invisibly integrated into living room furniture. We introduce capacitive imaging, investigating the use of computer vision methods to track hand and arm positions and present several use cases for CapTap. In a user study we found that the system has average localization errors of 1.5cm at touch distance and 5cm at an elevation of 20cm above the table. The users found the system intuitive and interesting to use.

: http://publica.fraunhofer.de/documents/N-422266.html