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Proceedings of the 1st International Conference on AI for People: Towards Sustainable AI, CAIP 2021, 20-24 November 2021, Bologna, Italy

Research Article

Predicting Human Body Dimensions from Single Images: a first step in automatic malnutrition detection

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  • @INPROCEEDINGS{10.4108/eai.20-11-2021.2314166,
        author={Hezha  MohammedKhan and Marleen  Balvert and Cicek  Guven and Eric  Postma},
        title={Predicting Human Body Dimensions from Single Images: a first step in automatic malnutrition detection},
        proceedings={Proceedings of the 1st International Conference on AI for People: Towards Sustainable AI, CAIP 2021, 20-24 November 2021, Bologna, Italy},
        publisher={EAI},
        proceedings_a={CAIP},
        year={2021},
        month={12},
        keywords={convolutional neural networks hunger malnutrition human body shape},
        doi={10.4108/eai.20-11-2021.2314166}
    }
    
  • Hezha MohammedKhan
    Marleen Balvert
    Cicek Guven
    Eric Postma
    Year: 2021
    Predicting Human Body Dimensions from Single Images: a first step in automatic malnutrition detection
    CAIP
    EAI
    DOI: 10.4108/eai.20-11-2021.2314166
Hezha MohammedKhan1,*, Marleen Balvert1, Cicek Guven1, Eric Postma1
  • 1: Tilburg University, The Netherlands
*Contact email: h.h.mohammedkhan@tilburguniversity.edu

Abstract

Malnutrition in children accounts for 45% of child deaths globally. Automatic malnutrition detection from digital photos serves as a decision support tool for early detection of malnutrition in rural areas. We study the feasibility of estimating body-shape characteristics from images of human body shapes as a first step in automatic malnutrition detection. We generate multi-view images of male and female bodies from rendered digital 3D scans of human bodies. Using convolutional neural networks (CNNs), we estimated waist circumference and body height with a mean absolute error of 59 mm and 9 mm, respectively. The estimation error of waist circumference depends on viewpoint. We conclude that automatic malnutrition detection from single images seems feasible, provided one or more suitable viewpoints are used.

Keywords
convolutional neural networks hunger malnutrition human body shape
Published
2021-12-13
Publisher
EAI
http://dx.doi.org/10.4108/eai.20-11-2021.2314166
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