Abstract
In this work, we designed and provided a proof-of-concept study for a novel system that takes several anthro-pometric measurements (bust, waist, and hip circumferences) simultaneously using only two (frontal and side) 2D images of a human subject. The system has two components: a specific camera setup with lasers and image analysis software. Towards this purpose, we compare body measurements of the proposed system and manual measurements on a limited number of subjects. For automatic measurements, we took one frontal and one side image from each subject. Body segmentation and pose estimation are applied to these images using pre-trained deep neural networks. Using the laser positions on the image, pixel sizes are estimated in terms of physical length (ie. centimeter). Using physical widths of the bust, waist, and hip in the images, their circumferences are estimated automatically. On three subjects, we obtained less than 10% measurement error. We concluded that anthropometric measurements could be obtained using a camera and laser setup. However, the number of subjects should be increased with a more precise laser to determine a better margin for measurement error.
Original language | English |
---|---|
Title of host publication | Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 251-256 |
Number of pages | 6 |
ISBN (Electronic) | 9781665470100 |
DOIs | |
Publication status | Published - 2022 |
Event | 7th International Conference on Computer Science and Engineering, UBMK 2022 - Diyarbakir, Turkey Duration: 14 Sept 2022 → 16 Sept 2022 |
Publication series
Name | Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022 |
---|
Conference
Conference | 7th International Conference on Computer Science and Engineering, UBMK 2022 |
---|---|
Country/Territory | Turkey |
City | Diyarbakir |
Period | 14/09/22 → 16/09/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- anthropometry
- body segmentation
- pose estimation