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

Chutisant Kerdvibulvech, Hideo Saito

研究成果: Conference contribution

11 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルAdvances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings
出版社Springer Verlag
ページ625-638
ページ数14
ISBN(印刷版)9783540771289
DOI
出版ステータスPublished - 2007
イベント2nd Pacific Rim Symposium on Image and Video Technology, PSIVT 2007 - Santiago, Chile
継続期間: 2007 12 172007 12 19

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4872 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

フィンガープリント 「Vision-based guitarist fingering tracking using a Bayesian classifier and particle filters」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル