Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Bare-hand human-computer interaction
Proceedings of the 2001 workshop on Perceptive user interfaces
Family ensemble: a collaborative musical edutainment system for children and parents
Proceedings of the 12th annual ACM international conference on Multimedia
Analyzing and Capturing Articulated Hand Motion in Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital violin tutor: an integrated system for beginning violin learners
Proceedings of the 13th annual ACM international conference on Multimedia
Visual methods for the retrieval of guitarist fingering
NIME '06 Proceedings of the 2006 conference on New interfaces for musical expression
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Automatic music transcription, in spite of decades of research, remains a challenging research problem. The traditional audio-only approach has yet to achieve a satisfactory performance for any computer-aided pedagogical system. Inspired by the high correlation between violin playing techniques (fingering, bowing) and the played acoustic notes, this paper presents a first attempt in visual analysis of violin fingering to compensate for the difficulties in audio-only music transcription. This is achieved by a robust multiple finger tracking algorithm and a string detection method that extract press, release, and fingertip position from the fingering video and automatically translate the fingering information into the played acoustic note, i.e., onset, offset, and pitches. Experimental results reveal high correctness in multiple finger tracking and string detection, thus paving the way for an improved audio-visual violin transcription system.