Sources of variation in the 3dMDface and Vectra H1 3D facial imaging systems

Julie D. White, Alejandra Ortega-Castrillon, Ciara Virgo, Karlijne Indencleef, Hanne Hoskens, Mark D. Shriver, Peter Claes

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

As technology advances and collaborations grow, our ability to finely quantify and explore morphological variation in 3D structures can enable important discoveries and insights into clinical, evolutionary, and genetic questions. However, it is critical to explore and understand the relative contribution of potential sources of error to the structures under study. In this study, we isolated the level of error in 3D facial images attributable to four sources, using the 3dMDface and Vectra H1 camera systems. When the two camera systems are used separately to image human participants, this analysis finds an upper bound of error potentially introduced by the use of the 3dMDface or Vectra H1 camera systems, in conjunction with the MeshMonk registration toolbox, at 0.44 mm and 0.40 mm, respectively. For studies using both camera systems, this upper bound increases to 0.85 mm, on average, and there are systematic differences in the representation of the eyelids, nostrils, and mouth by the two camera systems. Our results highlight the need for careful assessment of potential sources of error in 3D images, both in terms of magnitude and position, especially when dealing with very small measurements or performing many tests.

Original languageEnglish (US)
Article number4443
JournalScientific reports
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2020

All Science Journal Classification (ASJC) codes

  • General

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