# Automatic Estimation of Anthropometric Human Body Measurements

arXiv: https://arxiv.org/abs/2112.11992 · HTML: https://mlsanity.com/paper/2112.11992/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 22 references that are in the map.
- First posted on arXiv 22 Dec 2021.

## Builds on (most cited first, 7 of 7)

- [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](https://mlsanity.com/paper/1612.00593/) (2016)
- [PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds](https://mlsanity.com/paper/1901.01060/) (2019)
- [Anthropometric clothing measurements from 3D body scans](https://mlsanity.com/paper/1911.00694/) (2019)
- [Learning Anthropometry from Rendered Humans](https://mlsanity.com/paper/2101.02515/) (2021)
- [CALVIS: chest, waist and pelvis circumference from 3D human body meshes as ground truth for deep learning](https://mlsanity.com/paper/2003.00834/) (2020)
- [A Neural Anthropometer Learning from Body Dimensions Computed on Human 3D Meshes](https://mlsanity.com/paper/2110.04064/) (2021)
- [RGB-D-based Framework to Acquire, Visualize and Measure the Human Body for Dietetic Treatments](https://mlsanity.com/paper/2007.00981/) (2020)

## Built on by (most cited first, 4 of 4)

- [Estimation of 3D Body Shape and Clothing Measurements from Frontal- and Side-view Images](https://mlsanity.com/paper/2205.14347/) (2022)
- [Pose-independent 3D Anthropometry from Sparse Data](https://mlsanity.com/paper/2501.06014/) (2025)
- [Effect of Gender, Pose and Camera Distance on Human Body Dimensions Estimation](https://mlsanity.com/paper/2205.12028/) (2022)
- [Automated Deep Learning Estimation of Anthropometric Measurements for Preparticipation Cardiovascular Screening](https://mlsanity.com/paper/2512.06434/) (2025)

## Abstract (arXiv)

Research tasks related to human body analysis have been drawing a lot of attention in computer vision area over the last few decades, considering its potential benefits on our day-to-day life. Anthropometry is a field defining physical measures of a human body size, form, and functional capacities. Specifically, the accurate estimation of anthropometric body measurements from visual human body data is one of the challenging problems, where the solution would ease many different areas of applications, including ergonomics, garment manufacturing, etc. This paper formulates a research in the field of deep learning and neural networks, to tackle the challenge of body measurements estimation from various types of visual input data (such as 2D images or 3D point clouds). Also, we deal with the lack of real human data annotated with ground truth body measurements required for training and evaluation, by generating a synthetic dataset of various human body shapes and performing a skeleton-driven annotation.