Study of Tracking the Guitar Neck by Perspective Transformation in Video Sequences for Guitar Plays

Abstract

Towards the actualization of computer teachers that can supervise guitar plays, this paper proposes an algorithm to track the position of the fretboard from the video of guitar plays. In this paper, we use the Shi-Tomasi method to detect the corners of the fretboard as feature points and track the detected points using the Lucus-Kanade (LK) method. However, during the guitar plays, the performer's fingers frequently overlap the fretboard; thus, the feature points cannot be tracked accurately. Therefore, using the RANSAC algorithm, perspective transformation matrix is obtained from the feature points between the two consecutive frames, so that the fretboard can be tracked accurately. By using the different numbers of feature points 20, 30, 40 for the experiments, the best tracking results were obtained when 30 points were used. At that time, the processing time per frame was 7.3 seconds, and the error of the estimated position of the fretboard was 4.9 mm.