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A Bottom-Up Method for Pose Detection of Multiple People on Real-Time Video

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Pattern Recognition and Information Processing (PRIP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1562))

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Abstract

This article describes a realtime algorithm to determine a person’s posture at a certain point in time.

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References

  1. Sun, M., Savarese, S.: Articulated part-based model for joint object detection and pose estimation. In: ICCV (2011)

    Google Scholar 

  2. West, D.B.: Introduction to Graph Theory, vol. 2. Prentice Hall, Upper Saddle River (2001)

    Google Scholar 

  3. Weil, S.E., Ramakrishna, V., Kanade, T., Sheikh, Y.: Convolutional pose machines. In: CVPR (2016)

    Google Scholar 

  4. Yang, Y., Ramanan, D.: Articulated human detection with flexible mixtures of parts. In: TPAMI (2013)

    Google Scholar 

  5. Newell, A., Yang, K., Deng, J.: Stacked hourglass networks for human pose estimation. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9912, pp. 483–499. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46484-8_29

    Chapter  Google Scholar 

  6. Pishchulin, L., et al.: DeepCut: joint subset partition and labeling for multi person pose estimation. In: CVPR (2016)

    Google Scholar 

  7. Insafutdinov, E., Pishchulin, L., Andres, B., Andriluka, M., Schiele, B.: DeeperCut: a deeper, stronger, and faster multi-person pose estimation model. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9910, pp. 34–50. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46466-4_3

    Chapter  Google Scholar 

  8. Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740–755. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10602-1_48

    Chapter  Google Scholar 

  9. Chen, X., Yuille, A.: Articulated pose estimation by a graphical model with image dependent pairwise relations. In: NIPS (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Minsk, Belarus

    Aliaksandr Leunikau

  2. Faculty of Applied Mathematics and Computer Science, Belarusian State University, Minsk, Belarus

    Alexander Nedzved

  3. Department of Intelligent Information Systems, United Institute of Informatics Problems of NAS Belarus, Minsk, Belarus

    Alexei Belotserkovsky

  4. Belarusian State University, Minsk, Republic of Belarus

    Stanislav Sholtanyuk

Authors
  1. Aliaksandr Leunikau
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  2. Alexander Nedzved
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  3. Alexei Belotserkovsky
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  4. Stanislav Sholtanyuk
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Corresponding author

Correspondence to Alexander Nedzved .

Editor information

Editors and Affiliations

  1. United Institute of Informatics Problems of The National Academy of Sciences of Belarus, Minsk, Belarus

    Alexander V. Tuzikov

  2. United Institute of Informatics Problems of The National Academy of Sciences of Belarus, Minsk, Belarus

    Alexei M. Belotserkovsky

  3. Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus

    Marina M. Lukashevich

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Leunikau, A., Nedzved, A., Belotserkovsky, A., Sholtanyuk, S. (2022). A Bottom-Up Method for Pose Detection of Multiple People on Real-Time Video. In: Tuzikov, A.V., Belotserkovsky, A.M., Lukashevich, M.M. (eds) Pattern Recognition and Information Processing. PRIP 2021. Communications in Computer and Information Science, vol 1562. Springer, Cham. https://doi.org/10.1007/978-3-030-98883-8_14

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  • DOI: https://doi.org/10.1007/978-3-030-98883-8_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-98882-1

  • Online ISBN: 978-3-030-98883-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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