%0 Online Multimedia %A Silvester, Christopher %A Hillson, Simon %D 2019 %T 3D Dental models generated using Focus-stacked SfM Photogrammetry %U https://rdr.ucl.ac.uk/articles/media/3D_Dental_models_generated_using_Focus-stacked_SfM_Photogrammetry/9939533 %R 10.5522/04/9939533.v1 %2 https://rdr.ucl.ac.uk/ndownloader/files/17895605 %2 https://rdr.ucl.ac.uk/ndownloader/files/17895635 %2 https://rdr.ucl.ac.uk/ndownloader/files/17895638 %2 https://rdr.ucl.ac.uk/ndownloader/files/17895608 %2 https://rdr.ucl.ac.uk/ndownloader/files/17895611 %2 https://rdr.ucl.ac.uk/ndownloader/files/17915423 %2 https://rdr.ucl.ac.uk/ndownloader/files/17915426 %2 https://rdr.ucl.ac.uk/ndownloader/files/17915429 %2 https://rdr.ucl.ac.uk/ndownloader/files/17915432 %K 3D models %K Teeth %K photogrammetric 3 D models %K Focus Stacking %K Anthropology %K Archaeology %X Lower molar rows of anatomically modern humans generated using focus stacked structure from motion photogrammetry. Individuals are from St. Michael's Litten, Chichester, post-medieval assemblage (AD1550-1900). Each perspective was captured using between 20-30 optical slices of different focal depth. These were combined using Helicon Focus software. The full-focus images produced were exported into Agisoft Metashape for 3D model generation.
The specimen numbers correspond to the skeleton numbers of each individual. The site code for St. Michael's Litten is ESC11. These structure-from-motion 3D dental models were assessed alongside 3D models generated using a structured light scanner to determine their fidelity. The results of this research are presented the article "A critical assessment of the potential for Structure-from-Motion photogrammetry to produce high fidelity 3D Dental Models" under review in the American Journal of Physical Anthropology. The paper aimed to determine whether dental models generated using photogrammetry could be used to perform dental macrowear analysis. All 3D models assessed, and the photographs used to generate the models, are available from the UCL research data repository.


%I University College London