Capacitive Sensor-Based Hand Gesture Recognition in Ambient Intelligence Scenarios
Key: BDK13-1
Author: Andreas Braun, Tim Dutz, Felix Kamieth
Date: May 2013
Kind: In proceedings
Publisher: ACM
Book title: PETRA '13 - Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments
Abstract: Input devices based on arrays of capacitive proximity sensors allow the tracking of a user’s hands in three dimensions. They can be hidden behind materials such as wood, wool or plastics without limiting their functionality, making them ideal for application in Ambient Intelligence (AmI) scenarios. Most gesture recognition frameworks are targeted towards classical input devices and interpret two-dimensional data. In this work, we present a concept for adapting classical gesture recognition methods for capacitive input devices by realizing an extension of the feature set to three dimensional input data. This allows more robust gesture recognition for free-space interaction and training specific to capacitive input devices. We have implemented this concept in a prototypical setup and tested the device in various Ambient Intelligence scenarios, ranging from manipulating home appliances to controlling multimedia applications.
View Full paper (PDF) | Download Full paper (PDF)

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, not withstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.