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Non-Invasive Sensing And Gesture Control For Pitched Percussion Hyper-Instruments Using The Kinect

Authors: Shawn Trail; Michael Dean; Gabrielle Odowichuk; Tiago Fernandes Tavares; Peter F. Driessen; W. Andrew Schloss; George Tzanetakis;

Non-Invasive Sensing And Gesture Control For Pitched Percussion Hyper-Instruments Using The Kinect

Abstract

Hyper-instruments extend traditional acoustic instruments with sensing technologies that capture digitally subtle and sophisticated aspects of human performance. They leverage the long training and skills of performers while simultaneously providing rich possibilities for digital control. Many existing hyper-instruments suffer from being one of a kind instruments that require invasive modifications to the underlying acoustic instrument. In this paper we focus on the pitched percussion family and describe a non-invasive sensing approach for extending them to hyper-instruments. Our primary concern is to retain the technical integrity of the acoustic instrument and sound production methods while being able to intuitively interface the computer. This is accomplished by utilizing the Kinect sensor to track the position of the mallets without any modification to the instrument which enables easy and cheap replication of the pro-posed hyper-instrument extensions. In addition we describe two approaches to higher-level gesture control that remove the need for additional control devices such as foot pedals and fader boxes that are frequently used in electro-acoustic performance. This gesture control integrates more organically with the natural flow of playing the instrument providing user selectable control over filter parameters, synthesis, sampling, sequencing, and improvisation using a commer-cially available low-cost sensing apparatus.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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