# Automatic 3D modelling of craniofacial form

arXiv: https://arxiv.org/abs/1601.05593 · HTML: https://mlsanity.com/paper/1601.05593/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jan 2016.

## Built on by (most cited first, 1 of 1)

- [Hologram: Realtime Holographic Overlays via LiDAR Augmented Reconstruction](https://mlsanity.com/paper/2405.07178/) (2024)

## Abstract (arXiv)

Three-dimensional models of craniofacial variation over the general population are useful for assessing pre- and post-operative head shape when treating various craniofacial conditions, such as craniosynostosis. We present a new method of automatically building both sagittal profile models and full 3D surface models of the human head using a range of techniques in 3D surface image analysis; in particular, automatic facial landmarking using supervised machine learning, global and local symmetry plane detection using a variant of trimmed iterative closest points, locally-affine template warping (for full 3D models) and a novel pose normalisation using robust iterative ellipse fitting. The PCA-based models built using the new pose normalisation are more compact than those using Generalised Procrustes Analysis and we demonstrate their utility in a clinical case study.