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

Zhao Wang, Jun Ohya

    Research output: Contribution to journalConference article

    1 Citation (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 languageEnglish
    JournalIS and T International Symposium on Electronic Imaging Science and Technology
    VolumePart F129943
    DOIs
    Publication statusPublished - 2016 Jan 1
    EventImage Processing: Algorithms and Systems XIV 2016 - San Francisco, United States
    Duration: 2016 Feb 142016 Feb 18

    Fingerprint

    Teaching
    education
    modules
    Lighting
    illumination
    Monitoring

    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

    Cite this

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

    AU - Wang, Zhao

    AU - Ohya, Jun

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    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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