Vision-Based Detection of Guitar Players' Fingertips Without Markers

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Vision-Based Detection of Guitar Players' Fingertips Without Markers
This paper proposes a vision-based method for detecting the positions of fingertips of a hand playing a guitar. We detect the skin color of a guitar player’s hand by using on-line adaptation of color probabilities and a Bayesian classifier which can cope with considerable illumination changes and a dynamic background. The results of hand segmentation are used to train an artificial neural network. A set of Gabor filters is utilized to compute a lower-dimensional representation of the image. Then an LLM (Local-Linear-Mapping)-network is applied to map and estimate fingertip positions smoothly. The system enables us to visually detect the fingertips even when the fingertips are in front of skin-colored surfaces and/or when the fingers are not fully stretched out. Representative experimental results are also presented. Keywords--- Fingertip Detection of Guitar Player, Bayesian Classifier, Gabor Filter, Local Linear Mapping Network
Chutisant Kerdvibulvech, Hideo Saito
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Authors Chutisant Kerdvibulvech, Hideo Saito
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