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Updated: Jul 5, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors.

Byoung-Keon D Park¹, Hayoung Jung¹, Sheila M Ebert¹

¹Biosciences Group, University of Michigan Transportation Research Institute, Ann Arbor, MI 48109, USA.

Sensors (Basel, Switzerland)

|March 13, 2024

Summary

This summary is machine-generated.

A new system using depth cameras accurately measures clothed human body dimensions. This rapid anthropometric method reduces time and cost compared to traditional techniques.

Keywords:

3D anthropometry ANSUR body characterization body dimension measurement clothed scan measurement inscribed fit whole-body scanning

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Area of Science:

Human factors engineering
Biomedical engineering
Computer vision

Background:

Accurate human body dimension measurement is vital for engineering and product design.
Traditional anthropometric methods are time-consuming.
Current 3D scanning requires specific attire, raising cost and privacy concerns.

Purpose of the Study:

To develop a rapid, low-cost measurement system for human body dimensions.
To address limitations of manual and typical 3D scanning anthropometry.
To enable accurate measurement of clothed individuals.

Main Methods:

Development of a measurement system using portable, low-cost depth cameras.
Application of a model-based method, Inscribed Fitting, to point-cloud data.
Evaluation using manual measurements and system scans on 144 young adults with military ensembles.

Main Results:

The system accurately estimates body characteristics from depth camera data.
Prediction accuracy for clothed scans was comparable to minimally clad scans.
The developed system significantly reduces measurement time compared to manual and typical scanning methods.

Conclusions:

The novel depth camera system provides accurate anthropometric data for clothed individuals.
This approach offers a faster, more cost-effective, and privacy-conscious alternative to existing methods.
Enables efficient body dimension data acquisition for diverse populations and applications.