Title :
Retrieval of guitarist fingering information using computer vision
Author :
Scarr, Joseph ; Green, Richard
Author_Institution :
Dept. of Comput. Sci. & Software Eng., Univ. of Canterbury, Christchurch, New Zealand
Abstract :
Writing musical notation for guitar, otherwise known as tablature (or colloquially, “tab”) can be a tedious and time-consuming task when performed by hand. Software exists that can detect the pitch of a signal emitted from a musical instrument, but this is insufficient for guitar tablature which also requires spatial information. Previous vision-based methods had low accuracy rates and required the camera to be fixed to the guitar neck. In this paper we propose an algorithm that uses a markerless approach to successfully locate a guitar fretboard in a webcam image, normalise it and detect the individual locations of the guitarist´s fretting fingers. Preliminary testing of this system shows that it is more accurate at note recognition than existing methods which require a camera mounted on the guitar neck.
Keywords :
computer vision; image recognition; image retrieval; music; musical instruments; computer vision; guitar fretboard; guitar neck; guitar tablature; guitarist fingering information retrieval; markerless approach; musical instrument; musical notation writing; note recognition; webcam image; Algorithm design and analysis; Cameras; Computer vision; Equations; Image edge detection; Neck; Transforms; automatic transcription; computer vision; guitar;
Conference_Titel :
Image and Vision Computing New Zealand (IVCNZ), 2010 25th International Conference of
Conference_Location :
Queenstown
Print_ISBN :
978-1-4244-9629-7
DOI :
10.1109/IVCNZ.2010.6148852