Anne-Marie Burns
This thesis presents a method to visually detect and recognize fingering gestures of the left hand of a guitarist. The choice of computer vision to perform that task is motivated by the absence of a satisfying method for realtime guitarist fingering detection. The development of this computer vision method follows preliminary manual and automated analyses of video recordings of a guitarist. These first analyses led to some important findings about the design methodology of such a system, namely the focus on the effective gesture, the consideration of the action of each individual finger, and a recognition system not relying
on comparison against a knowledge-base of previously learned fingering positions. Motivated by these results, studies on three important aspects of a complete fingering system were conducted. One study was on realtime finger-localization, another on string and fret detection, and the last on movement segmentation. Finally, these concepts were integrated into a prototype and a system for left-hand fingering detection was developed. Such a data acquisition system for fingering retrieval has uses in music theory, music education, automatic music and accompaniment generation and physical modeling.
Input Devices and Music Interaction Lab
Schulich School of Music
McGill University
Montr´eal, Qu´ebec, Canada
January 2007
Computer Vision Methods for Guitarist Left-Hand Fingering Recognition
