Vision-based detection of guitar players' fingertips without markers

Chutisant Kerdvibulvech, Hideo Saito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationComputer Graphics, Imaging and Visualisation
Subtitle of host publicationNew Advances, CGIV 2007
Pages419-424
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
EventComputer Graphics, Imaging and Visualisation: New Advances, CGIV 2007 - Bangkok, Thailand
Duration: 2007 Aug 132007 Aug 16

Publication series

NameComputer Graphics, Imaging and Visualisation: New Advances, CGIV 2007

Other

OtherComputer Graphics, Imaging and Visualisation: New Advances, CGIV 2007
CountryThailand
CityBangkok
Period07/8/1307/8/16

Keywords

  • Bayesian classifier
  • Fingertip detection of guitar player
  • Gabor filter
  • Local linear mapping network

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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  • Cite this

    Kerdvibulvech, C., & Saito, H. (2007). Vision-based detection of guitar players' fingertips without markers. In Computer Graphics, Imaging and Visualisation: New Advances, CGIV 2007 (pp. 419-424). [4293708] (Computer Graphics, Imaging and Visualisation: New Advances, CGIV 2007). https://doi.org/10.1109/CGIV.2007.88