Body shape calculator: Understanding the type of body shapes from anthropometric measurements

Shintami Chusnul Hidayati, Yeni Anistyasari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Human body shape, which describes the contours of the body figure as well as the distribution of muscles and fat, contains a rich source of information, from health issues to aesthetic presentation of fashion styles. However, most of the existing methods for estimating body types are derived from subjective measures, which are susceptible to multiple biases. Determining the type of body shapes is still a challenging analytical task, for which open questions remain regarding good feature representation and classification methods, given noisy and imbalanced real-world data. In this work, we propose a novel body type recognition framework based on anthropometric measurements, which integrates label filtering and pseudo-feature synthesis modules. Label filtering is proposed to identify and filter out potentially noisy labels during classifier training, while pseudo-feature is generated to improve feature representation. Experimental results on the collected dataset from online feeds demonstrate the effectiveness of the approach compared to the state-of-the-art baselines.

Original languageEnglish
Title of host publicationICMR 2021 - Proceedings of the 2021 International Conference on Multimedia Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages461-465
Number of pages5
ISBN (Electronic)9781450384636
DOIs
Publication statusPublished - 24 Aug 2021
Event11th ACM International Conference on Multimedia Retrieval, ICMR 2021 - Taipei, Taiwan, Province of China
Duration: 16 Nov 202119 Nov 2021

Publication series

NameICMR 2021 - Proceedings of the 2021 International Conference on Multimedia Retrieval

Conference

Conference11th ACM International Conference on Multimedia Retrieval, ICMR 2021
Country/TerritoryTaiwan, Province of China
CityTaipei
Period16/11/2119/11/21

Keywords

  • Body shapes
  • Classification
  • Information extraction
  • Label filtering
  • Pseudo-feature

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