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Speed-Up 3D Human Pose Estimation Task Using Sub-spacing Approach

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10752))

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Abstract

This paper tackles the problem of reconstructing 3D human poses from given 2D landmarks, which is still an ill-posed problem. The existing works have successfully applied Active Shape Model approach to estimate 3D human poses, but the execution time is quite high. In this paper, we propose a speed-up method by separating data into subspaces to reduce the execution time of existing methods in two steps: (i) Predicting the subspace that the need-estimated 3D shape could belong to. (ii) Estimating 3D shape from given 2D landmarks and predefined basis shapes of this subspace. Compare to existing works; our approach shows a significant reduction in computational time.

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Acknowledgment

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2017-2016-0-00318) supervised by the IITP (Institute for Information & communications Technology Promotion).

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Authors and Affiliations

  1. School of Electrical Engineering, University of Ulsan, Ulsan, Korea

    Van-Thanh Hoang & Kang-Hyun Jo

Authors
  1. Van-Thanh Hoang
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  2. Kang-Hyun Jo
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Corresponding author

Correspondence to Van-Thanh Hoang .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Hoang, VT., Jo, KH. (2018). Speed-Up 3D Human Pose Estimation Task Using Sub-spacing Approach. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10752. Springer, Cham. https://doi.org/10.1007/978-3-319-75420-8_52

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  • DOI: https://doi.org/10.1007/978-3-319-75420-8_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75419-2

  • Online ISBN: 978-3-319-75420-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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