Vision-based guitarist fingering tracking using a Bayesian classifier and particle filters

Chutisant Kerdvibulvech, Hideo Saito

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

11 Citations (Scopus)

Abstract

This paper presents a vision-based method for tracking guitar fingerings played by guitar players from stereo cameras. We propose a novel framework for colored finger markers tracking by integrating a Bayesian classifier into particle filters, with the advantages of performing automatic track initialization and recovering from tracking failures in a dynamic background. ARTag (Augmented Reality Tag) is utilized to calculate the projection matrix as an online process which allow guitar to be moved while playing. By using online adaptation of color probabilities, it is also able to cope with illumination changes.

Original languageEnglish
Title of host publicationAdvances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings
PublisherSpringer Verlag
Pages625-638
Number of pages14
ISBN (Print)9783540771289
DOIs
Publication statusPublished - 2007 Jan 1
Event2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007 - Santiago, Chile
Duration: 2007 Dec 172007 Dec 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4872 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007
CountryChile
CitySantiago
Period07/12/1707/12/19

Keywords

  • Augmented reality tag
  • Bayesian classifier
  • Guitarist fingering tracking
  • Particle filters

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kerdvibulvech, C., & Saito, H. (2007). Vision-based guitarist fingering tracking using a Bayesian classifier and particle filters. In Advances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings (pp. 625-638). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4872 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-77129-6_54