International Computer Music Conference 2016 Papers Track

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Detecting Pianist Hand Posture Mistakes for Virtual Piano Tutoring

Incorrect hand posture is known to cause fatigue and hand injuries in pianists of all levels. Our research is intended to reduce these problems through new methods of providing direct feedback to piano students during their daily practice. This paper presents an approach to detect hand posture in RGB-D recordings of pianists' hands while practicing for use in a virtual music tutor. We do so through image processing and machine learning. To test this approach we collect data by recording the hands of two pianists during standard piano exercises. Preliminary results show the effectiveness of our methods.

Author(s):

David Johnson    
Department of Computer Science
University of Victoria
Canada

Isabelle Dufour    
Department of Computer Science
University of Victoria
Canada

Daniela Damian    
Department of Computer Science
University of Victoria
Canada

George Tzanetakis    
Department of Computer Science
University of Victoria
Canada

 

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