Tracking the guitarist’s fingers as well as recognizing pressed chords from a video sequence

Zhao Wang; Jun Ohya

doi:10.2352/ISSN.2470-1173.2016.15.IPAS-047

Tracking the guitarist’s fingers as well as recognizing pressed chords from a video sequence

Zhao Wang, Jun Ohya

Research output: Contribution to journal › Conference article › peer-review

3 Citations (Scopus)

Abstract

Towards the actualization of an autonomous guitar teaching system, this paper proposes the following two video analysis based methods: (1) pressed chord recognition and (2) fingertip tracking. For (1), an algorithm that can extract finger contours and chord changes is proposed so that the chords pressed by the guitar player are recognized. For (2), an algorithm that can track the fingertips by continuously monitoring the appearance and disappearance of the regions of fingertip candidates is proposed. Experimental results demonstrate that the proposed two modules are robust enough under complex contexts such as complicated background and different illumination conditions. Promising results were obtained for accurate tracking of fingertips and for accurate recognition of pressed chords.

Original language	English
Journal	IS and T International Symposium on Electronic Imaging Science and Technology
Volume	Part F129943
DOIs	https://doi.org/10.2352/ISSN.2470-1173.2016.15.IPAS-047
Publication status	Published - 2016 Jan 1
Event	Image Processing: Algorithms and Systems XIV 2016 - San Francisco, United States Duration: 2016 Feb 14 → 2016 Feb 18

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Science Applications
Human-Computer Interaction
Software
Electrical and Electronic Engineering
Atomic and Molecular Physics, and Optics

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10.2352/ISSN.2470-1173.2016.15.IPAS-047

Cite this

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title = "Tracking the guitarist{\textquoteright}s fingers as well as recognizing pressed chords from a video sequence",

abstract = "Towards the actualization of an autonomous guitar teaching system, this paper proposes the following two video analysis based methods: (1) pressed chord recognition and (2) fingertip tracking. For (1), an algorithm that can extract finger contours and chord changes is proposed so that the chords pressed by the guitar player are recognized. For (2), an algorithm that can track the fingertips by continuously monitoring the appearance and disappearance of the regions of fingertip candidates is proposed. Experimental results demonstrate that the proposed two modules are robust enough under complex contexts such as complicated background and different illumination conditions. Promising results were obtained for accurate tracking of fingertips and for accurate recognition of pressed chords.",

author = "Zhao Wang and Jun Ohya",

year = "2016",

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doi = "10.2352/ISSN.2470-1173.2016.15.IPAS-047",

language = "English",

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note = "Image Processing: Algorithms and Systems XIV 2016 ; Conference date: 14-02-2016 Through 18-02-2016",

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TY - JOUR

T1 - Tracking the guitarist’s fingers as well as recognizing pressed chords from a video sequence

AU - Wang, Zhao

AU - Ohya, Jun

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Towards the actualization of an autonomous guitar teaching system, this paper proposes the following two video analysis based methods: (1) pressed chord recognition and (2) fingertip tracking. For (1), an algorithm that can extract finger contours and chord changes is proposed so that the chords pressed by the guitar player are recognized. For (2), an algorithm that can track the fingertips by continuously monitoring the appearance and disappearance of the regions of fingertip candidates is proposed. Experimental results demonstrate that the proposed two modules are robust enough under complex contexts such as complicated background and different illumination conditions. Promising results were obtained for accurate tracking of fingertips and for accurate recognition of pressed chords.

AB - Towards the actualization of an autonomous guitar teaching system, this paper proposes the following two video analysis based methods: (1) pressed chord recognition and (2) fingertip tracking. For (1), an algorithm that can extract finger contours and chord changes is proposed so that the chords pressed by the guitar player are recognized. For (2), an algorithm that can track the fingertips by continuously monitoring the appearance and disappearance of the regions of fingertip candidates is proposed. Experimental results demonstrate that the proposed two modules are robust enough under complex contexts such as complicated background and different illumination conditions. Promising results were obtained for accurate tracking of fingertips and for accurate recognition of pressed chords.

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DO - 10.2352/ISSN.2470-1173.2016.15.IPAS-047

M3 - Conference article

SN - 2470-1173

VL - Part F129943

JO - IS and T International Symposium on Electronic Imaging Science and Technology

JF - IS and T International Symposium on Electronic Imaging Science and Technology

T2 - Image Processing: Algorithms and Systems XIV 2016

Y2 - 14 February 2016 through 18 February 2016

ER -

Tracking the guitarist’s fingers as well as recognizing pressed chords from a video sequence

Abstract

ASJC Scopus subject areas

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