We present a method for the analysis of the finger-string interaction in guitar performances and the computation of fine actions during the plucking gesture. The method is based on Motion Capture using high-speed cameras that can track the position of reflective markers placed on the guitar and fingers, in combination with audio analysis. A major problem inherent in optical motion capture is that of marker occlusion and, in guitar playing, it is the right hand of the guitarist that is extremely difficult to capture, especially during the plucking process, where the track of the markers at the fingertips is lost very frequently. This work presents two models that allow the reconstruction of the position of occluded markers: a rigid-body model to track the motion of the guitar strings and a flexible-body model to track the motion of the hands. In combination with audio analysis (onset and pitch detection), the method can estimate a comprehensive set of sound control features that include the plucked string, the plucking finger, and the characteristics of the plucking gesture in the phases of contact, pressure and release (e.g., position, timing, velocity, direction, or string displacement).

This work has been sponsored by the European Union Horizon 2020 research and innovation program under grant agreement No. 688269 (TELMI project) and Beatriu de Pinos grant 2010 BP-A 00209 by the Catalan Research Agency (AGAUR).