Three-dimensional facial capture using a custom-built photogrammetry setup
| Autor: | Alejandra Ortega-Castrillon, Peter Claes, Hanne Hoskens, Hans L L Wellens, Anne Marie Kuijpers-Jagtman |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Mean squared error
Computer science ACCURACY Orthodontics ANTHROPOMETRIC PRECISION Face scanning VALIDATION 03 medical and health sciences 0302 clinical medicine Imaging Three-Dimensional FACE REPRODUCIBILITY three-dimensional) Superimposition stereophotogrammetry Computer vision Polygon mesh 610 Medicine & health Dental Implants Ground truth business.industry 030206 dentistry 3D imaging (imaging Photogrammetry Face (geometry) Artificial intelligence Procrustes analysis business 030217 neurology & neurosurgery 3D imaging (imaging three-dimensional) |
| Zdroj: | American Journal of Orthodontics and Dentofacial Orthopedics, 158(2), 286-299. MOSBY-ELSEVIER |
| ISSN: | 0889-5406 |
| DOI: | 10.1016/j.ajodo.2020.01.016 |
| Popis: | INTRODUCTION: Although stereophotogrammetry is increasingly popular for 3-dimensional face scanning, commercial solutions remain quite expensive, limiting its accessibility. We propose a more affordable, custom-built photogrammetry setup (Stereo-Face 3D, SF3D) and evaluate its variability within and between systems. METHODS: Twenty-nine subjects and a mannequin head were imaged 3 times using SF3D and a commercially available system. An anthropometric mask was mapped viscoelastically onto the reconstructed meshes using MeshMonk (https://github.com/TheWebMonks/meshmonk). Within systems, shape variability was determined by calculating the root-mean-square error (RMSE) of the Procrustes distance between each of the subject's 3 scans and the subject's ground truth (calculated by averaging the mappings after a nonscaled generalized Procrustes superimposition). Intersystem variability was determined by similarly comparing the ground truth mappings of both systems. Two-factor Procrustes analysis of variance was used to partition the intersystem shape variability to understand the source of the discrepancies between the facial shapes acquired by both systems. RESULTS: The RMSEs of the within-system shape variability for 3dMDFace and SF3D were 0.52 ± 0.07 mm and 0.44 ± 0.16 mm, respectively. The corresponding values for the mannequin head were 0.42 ± 0.02 mm and 0.29 ± 0.03 mm, respectively. The between-systems RMSE was 1.6 ± 0.34 mm for the study group and 1.38 mm for the mannequin head. A 2-factor analysis indicated that variability attributable to the system was expressed mainly at the upper eyelids, nasal tip and alae, and chin areas. CONCLUSIONS: The variability values of the custom-built setup presented here were competitive to a state-of-the-art commercial system at a more affordable level of investment. ispartof: American Journal Of Orthodontics And Dentofacial Orthopedics vol:158 issue:2 pages:286-299 ispartof: location:United States status: Published online |
| Databáze: | OpenAIRE |
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