Estimating 2D Upper Body Poses from Monocular Images

Jeroen Broekhuijsen, Ronald Walter Poppe, Mannes Poel

    Research output: Book/ReportReportProfessional

    22 Downloads (Pure)

    Abstract

    Automatic estimation and recognition of poses from video allows for a whole range of applications. The research described here is an important step towards automatic extraction of 3D poses. We describe our research to extract the 2D joint locations of the people in meeting videos. The key point of the research described here is that we generalize over variations in appearance of both people and scene. This results in a robust detection of 2D joint locations. For the detection of different limbs, we employ a number of limb locators. Each of these uses a different set of image features. We evaluate our work on two videos that have been recorded in the meeting context. Our results are promising, yielding an average error of approximately 3-5 cm per joint.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherCentrum voor Telematica en Informatie Technologie
    Number of pages12
    Publication statusPublished - 6 Sep 2006

    Publication series

    NameCTIT Technical Report Series
    PublisherUniversity of Twente, Centre for Telematics and Information Technology
    No.06-55
    ISSN (Print)1381-3625

    Keywords

    • EWI-6903
    • EC Grant Agreement nr.: FP6/506811
    • IR-66349
    • METIS-238676

    Cite this

    Broekhuijsen, J., Poppe, R. W., & Poel, M. (2006). Estimating 2D Upper Body Poses from Monocular Images. (CTIT Technical Report Series; No. 06-55). Enschede: Centrum voor Telematica en Informatie Technologie.
    Broekhuijsen, Jeroen ; Poppe, Ronald Walter ; Poel, Mannes. / Estimating 2D Upper Body Poses from Monocular Images. Enschede : Centrum voor Telematica en Informatie Technologie, 2006. 12 p. (CTIT Technical Report Series; 06-55).
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    abstract = "Automatic estimation and recognition of poses from video allows for a whole range of applications. The research described here is an important step towards automatic extraction of 3D poses. We describe our research to extract the 2D joint locations of the people in meeting videos. The key point of the research described here is that we generalize over variations in appearance of both people and scene. This results in a robust detection of 2D joint locations. For the detection of different limbs, we employ a number of limb locators. Each of these uses a different set of image features. We evaluate our work on two videos that have been recorded in the meeting context. Our results are promising, yielding an average error of approximately 3-5 cm per joint.",
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    Broekhuijsen, J, Poppe, RW & Poel, M 2006, Estimating 2D Upper Body Poses from Monocular Images. CTIT Technical Report Series, no. 06-55, Centrum voor Telematica en Informatie Technologie, Enschede.

    Estimating 2D Upper Body Poses from Monocular Images. / Broekhuijsen, Jeroen; Poppe, Ronald Walter; Poel, Mannes.

    Enschede : Centrum voor Telematica en Informatie Technologie, 2006. 12 p. (CTIT Technical Report Series; No. 06-55).

    Research output: Book/ReportReportProfessional

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    AU - Poppe, Ronald Walter

    AU - Poel, Mannes

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    N2 - Automatic estimation and recognition of poses from video allows for a whole range of applications. The research described here is an important step towards automatic extraction of 3D poses. We describe our research to extract the 2D joint locations of the people in meeting videos. The key point of the research described here is that we generalize over variations in appearance of both people and scene. This results in a robust detection of 2D joint locations. For the detection of different limbs, we employ a number of limb locators. Each of these uses a different set of image features. We evaluate our work on two videos that have been recorded in the meeting context. Our results are promising, yielding an average error of approximately 3-5 cm per joint.

    AB - Automatic estimation and recognition of poses from video allows for a whole range of applications. The research described here is an important step towards automatic extraction of 3D poses. We describe our research to extract the 2D joint locations of the people in meeting videos. The key point of the research described here is that we generalize over variations in appearance of both people and scene. This results in a robust detection of 2D joint locations. For the detection of different limbs, we employ a number of limb locators. Each of these uses a different set of image features. We evaluate our work on two videos that have been recorded in the meeting context. Our results are promising, yielding an average error of approximately 3-5 cm per joint.

    KW - EWI-6903

    KW - EC Grant Agreement nr.: FP6/506811

    KW - IR-66349

    KW - METIS-238676

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    Broekhuijsen J, Poppe RW, Poel M. Estimating 2D Upper Body Poses from Monocular Images. Enschede: Centrum voor Telematica en Informatie Technologie, 2006. 12 p. (CTIT Technical Report Series; 06-55).