ANTHROPOMETRIC METHODOLOGY OF CLASSIFICATION OF FEMALE BODIES FOR SIZE DEFINITION IN CLOTHING

Authors

DOI:

https://doi.org/10.24310/Idiseno.2022.v17i.14735

Keywords:

Anthropometry, statistical method, body shapes, 3D

Abstract

Knowledge of the human body is one of the great challenges in apparel design, the quality in the technical development of a garment arises from the understanding of the shapes, measurements, sizes, and proportions of the body which are the basis for developing the pattern in a garment.

Statistical methods and 3D technology are a very useful tool for the apparel industry, facilitating the capture and analysis of data from three-dimensional avatars associated with different body types.

The used method aims at the classification and identification of body shapes and typologies, developing the following stages: definition of reference values from population averages, definition of interval widths comparing sizes and measurements, calculation of differences in reference values, definition of the indicator related to the size of the person, obtaining the inter-measurements, and finally the classification of the body, which generated as a result seven typologies of bodies classified according to their shapes.

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Author Biographies

  • Jhon Fernando Jaramillo Taborda, Investigador
    Investigador
  • Jorge Andrés Cock Ramírez, Investigador
    Investigador
  • Marisol Osorio Beltrán, Investigador
    Investigador
  • Fabio Andrés Gaviria Londoño, Investigador
    Investigador
  • Maria Tatiana Cossio Posada, Investigador
    Investigador
  • Javier Rosique García, Investigador
    Investigador

References

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Published

2022-12-25

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How to Cite

Jaramillo Taborda, J. F., Cock Ramírez, J. A., Osorio Beltrán, M. ., Gaviria Londoño, F. A., Cossio Posada, M. T. ., & Rosique García, J. (2022). ANTHROPOMETRIC METHODOLOGY OF CLASSIFICATION OF FEMALE BODIES FOR SIZE DEFINITION IN CLOTHING. I+Diseño. Revista Científica De Investigación Y Desarrollo En Diseño, 17, 149-162. https://doi.org/10.24310/Idiseno.2022.v17i.14735