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  1. Proceedings of the 3rd International Workshop on Sensor-based Activity Recognition and Interaction (iWOAR '16)
  2. CapTap: combining capacitive gesture recognition and acoustic touch detection
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SmartMove: a smartwatch algorithm to distinguish between high- and low-amplitude motions as well as doffed-states by utilizing noise and sleep
Coping with variability in motion based activity recognition
Towards a situation model for assessing challenging behaviour of people with dementia
WeaRelaxAble: a wearable system to enhance stress resistance using various kinds of feedback stimuli
Activity recognition for physical therapy: fusing signal processing features and movement patterns
AGIS: automated tool detection & hand-arm vibration estimation using an unmodified smartwatch
okinesio: the development of open hardware for quantified self
CapTap: combining capacitive gesture recognition and acoustic touch detection
Tool support for the online annotation of sensor data

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CapTap: combining capacitive gesture recognition and acoustic touch detection

Content Provider ACM Digital Library
Author Krepp, Stefan Wichert, Reiner Rus, Silvia Kuijper, Arjan Zander-Walz, Sebastian Braun, Andreas
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.
Starting Page 1
Ending Page 6
Page Count 6
File Format PDF MP4
ISBN 9781450342452
DOI 10.1145/2948963.2948969
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-06-23
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Capacitive proximity sensors Gesture recognition Hidden interaction
Content Type Audio Text
Resource Type Article
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