Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors
Measuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensio...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-02-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/5/1350 |
| _version_ | 1797263895180607488 |
|---|---|
| author | Byoung-Keon D. Park Hayoung Jung Sheila M. Ebert Brian D. Corner Matthew P. Reed |
| author_facet | Byoung-Keon D. Park Hayoung Jung Sheila M. Ebert Brian D. Corner Matthew P. Reed |
| author_sort | Byoung-Keon D. Park |
| collection | DOAJ |
| description | Measuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensional (3D) whole-body scanning can be much faster, but 3D scanning typically requires subjects to change into tight-fitting clothing, which increases time and cost and introduces privacy concerns. To address these and other issues in current anthropometry techniques, a measurement system was developed based on portable, low-cost depth cameras. Point-cloud data from the sensors are fit using a model-based method, Inscribed Fitting, which finds the most likely body shape in the statistical body shape space and providing accurate estimates of body characteristics. To evaluate the system, 144 young adults were measured manually and with two levels of military ensembles using the system. The results showed that the prediction accuracy for the clothed scans remained at a similar level to the accuracy for the minimally clad scans. This approach will enable rapid measurement of clothed populations with reduced time compared to manual and typical scan-based methods. |
| first_indexed | 2024-04-25T00:20:16Z |
| format | Article |
| id | doaj.art-96c95a17066341169a65a8c724d774cd |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-25T00:20:16Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-96c95a17066341169a65a8c724d774cd2024-03-12T16:54:28ZengMDPI AGSensors1424-82202024-02-01245135010.3390/s24051350Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth SensorsByoung-Keon D. Park0Hayoung Jung1Sheila M. Ebert2Brian D. Corner3Matthew P. Reed4Biosciences Group, University of Michigan Transportation Research Institute, Ann Arbor, MI 48109, USABiosciences Group, University of Michigan Transportation Research Institute, Ann Arbor, MI 48109, USABiosciences Group, University of Michigan Transportation Research Institute, Ann Arbor, MI 48109, USACorner3d LLC, Bedford, VA 24523, USABiosciences Group, University of Michigan Transportation Research Institute, Ann Arbor, MI 48109, USAMeasuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensional (3D) whole-body scanning can be much faster, but 3D scanning typically requires subjects to change into tight-fitting clothing, which increases time and cost and introduces privacy concerns. To address these and other issues in current anthropometry techniques, a measurement system was developed based on portable, low-cost depth cameras. Point-cloud data from the sensors are fit using a model-based method, Inscribed Fitting, which finds the most likely body shape in the statistical body shape space and providing accurate estimates of body characteristics. To evaluate the system, 144 young adults were measured manually and with two levels of military ensembles using the system. The results showed that the prediction accuracy for the clothed scans remained at a similar level to the accuracy for the minimally clad scans. This approach will enable rapid measurement of clothed populations with reduced time compared to manual and typical scan-based methods.https://www.mdpi.com/1424-8220/24/5/13503D anthropometrybody dimension measurementANSURwhole-body scanninginscribed fitbody characterization |
| spellingShingle | Byoung-Keon D. Park Hayoung Jung Sheila M. Ebert Brian D. Corner Matthew P. Reed Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors Sensors 3D anthropometry body dimension measurement ANSUR whole-body scanning inscribed fit body characterization |
| title | Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors |
| title_full | Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors |
| title_fullStr | Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors |
| title_full_unstemmed | Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors |
| title_short | Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors |
| title_sort | efficient model based anthropometry under clothing using low cost depth sensors |
| topic | 3D anthropometry body dimension measurement ANSUR whole-body scanning inscribed fit body characterization |
| url | https://www.mdpi.com/1424-8220/24/5/1350 |
| work_keys_str_mv | AT byoungkeondpark efficientmodelbasedanthropometryunderclothingusinglowcostdepthsensors AT hayoungjung efficientmodelbasedanthropometryunderclothingusinglowcostdepthsensors AT sheilamebert efficientmodelbasedanthropometryunderclothingusinglowcostdepthsensors AT briandcorner efficientmodelbasedanthropometryunderclothingusinglowcostdepthsensors AT matthewpreed efficientmodelbasedanthropometryunderclothingusinglowcostdepthsensors |