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International Conference on Multimedia Modeling

MMM 2019: MultiMedia Modeling pp 567–577Cite as

A New Female Body Segmentation and Feature Localisation Method for Image-Based Anthropometry

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11295))

Abstract

An increasingly growing demand on the bespoke service for buying clothes online presents a new challenge of how to efficiently and precisely acquire anthropometric data of distant customers. The conventional 2D anthropometric methods are efficient but face a problem of imperfect body segmentation because they cannot automatically deal with arbitrary background. To address this problem this paper aimed at female anthropometry proposes to segment the female body out of an orthogonal photo pair with deep learning, and to extract a group of body feature points according to curvature and bending direction of the segmented body contour. With the located feature points we estimate six body parameters with two existing mathematical models and assess their pros and cons in this paper.

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Acknowledgements

This work was supported by the Open Research Fund of Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, People’s Republic of China

    Dan Wang, Yun Sheng & GuiXu Zhang

  2. The Department of Computer Science and Technology, East China Normal University, Shanghai, People’s Republic of China

    Dan Wang, Yun Sheng & GuiXu Zhang

Authors
  1. Dan Wang
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  2. Yun Sheng
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  3. GuiXu Zhang
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Corresponding author

Correspondence to Yun Sheng .

Editor information

Editors and Affiliations

  1. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece

    Ioannis Kompatsiaris

  2. EURECOM, Sophia Antipolis, France

    Benoit Huet

  3. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece

    Vasileios Mezaris

  4. Dublin City University, Dublin, Ireland

    Cathal Gurrin

  5. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Huang Cheng

  6. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece

    Stefanos Vrochidis

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Wang, D., Sheng, Y., Zhang, G. (2019). A New Female Body Segmentation and Feature Localisation Method for Image-Based Anthropometry. In: Kompatsiaris, I., Huet, B., Mezaris, V., Gurrin, C., Cheng, WH., Vrochidis, S. (eds) MultiMedia Modeling. MMM 2019. Lecture Notes in Computer Science(), vol 11295. Springer, Cham. https://doi.org/10.1007/978-3-030-05710-7_47

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  • DOI: https://doi.org/10.1007/978-3-030-05710-7_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05709-1

  • Online ISBN: 978-3-030-05710-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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