By the same authors

Automatic Modelling of 3D Craniofacial Form

Research output: Working paperPreprint

Standard

Automatic Modelling of 3D Craniofacial Form. / Pears, Nicholas Edwin; Duncan, Christian.

2016. p. 1-57.

Research output: Working paperPreprint

Harvard

Pears, NE & Duncan, C 2016 'Automatic Modelling of 3D Craniofacial Form' pp. 1-57. <http://arxiv.org/pdf/1601.05593.pdf>

APA

Pears, N. E., & Duncan, C. (2016). Automatic Modelling of 3D Craniofacial Form. (pp. 1-57). http://arxiv.org/pdf/1601.05593.pdf

Vancouver

Pears NE, Duncan C. Automatic Modelling of 3D Craniofacial Form. 2016 Jan 22, p. 1-57.

Author

Pears, Nicholas Edwin ; Duncan, Christian. / Automatic Modelling of 3D Craniofacial Form. 2016. pp. 1-57

Bibtex - Download

@techreport{022379539be24d94b9257be0f5d0eead,
title = "Automatic Modelling of 3D Craniofacial Form",
abstract = "Three-dimensional models of craniofacial variation over the general populationare 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 pro le 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 tting. 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.",
keywords = "3D shape modelling, Symmetry plane extraction, Automatic landmarking, 3D feature matching",
author = "Pears, {Nicholas Edwin} and Christian Duncan",
year = "2016",
month = jan,
day = "22",
language = "English",
pages = "1--57",
type = "WorkingPaper",

}

RIS (suitable for import to EndNote) - Download

TY - UNPB

T1 - Automatic Modelling of 3D Craniofacial Form

AU - Pears, Nicholas Edwin

AU - Duncan, Christian

PY - 2016/1/22

Y1 - 2016/1/22

N2 - Three-dimensional models of craniofacial variation over the general populationare 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 pro le 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 tting. 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.

AB - Three-dimensional models of craniofacial variation over the general populationare 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 pro le 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 tting. 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.

KW - 3D shape modelling, Symmetry plane extraction, Automatic landmarking, 3D feature matching

M3 - Preprint

SP - 1

EP - 57

BT - Automatic Modelling of 3D Craniofacial Form

ER -