SP-MORPH
Spectral Mesh Processing for Craniofacial Dysmorphology
| Coordinatore | DUBLIN CITY UNIVERSITY
Organization address
address: Glasnevin contact info |
| Nazionalità Coordinatore | Ireland [IE] |
| Totale costo | 191˙938 € |
| EC contributo | 191˙938 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2011-IEF |
| Funding Scheme | MC-IEF |
| Anno di inizio | 2012 |
| Periodo (anno-mese-giorno) | 2012-09-01 - 2014-08-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
DUBLIN CITY UNIVERSITY
Organization address
address: Glasnevin contact info |
IE (DUBLIN) | coordinator | 191˙938.20 |
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Obiettivo del progetto (Objective)
'There is heightened interest in the resolution and quantification of craniofacial dysmorphology based on: 1) its association with, and ability to inform on, diseases of early brain development, such as Down syndrome, fetal alcohol syndrome and schizophrenia; 2) increasing availability of 3D imaging technologies that overcome many of the limitations inherent to two-dimensional approaches. In this project, the candidate will develop techniques for the analysis of facial surfaces based on spectral decomposition methods. As opposed to traditional methods, based on a reduced set of landmark points, spectral mesh processing (SMP) allows analysis of the whole facial surface; recent work indicates its suitability for analysis of intrinsic properties of the object, such as symmetry, believed to be a crucial component of dysmorphology. As a novel and very active trend in computer graphics and vision, SMP still involves a number of important technical challenges for its use in engineering applications, where input data would usually need to undergo one or more pre-processing steps, often with the need for human intervention before such spectral methods can be used. The present proposal aims at addressing the above issues to develop highly automated algorithms for spectral analysis. This is expected to allow for increased precision in overall analysis, which is especially relevant in neuropsychiatric disorders, where craniofacial dysmorphology is considerably more subtle than, for example, in Down syndrome. The project will benefit greatly from the availability of a large and unique collection of facial scans acquired in the context of clinical studies of neuropsychiatric disorders of developmental origin, which guarantee the necessary test data for a thorough assessment of the techniques developed Wide interest in the literature regarding SMP suggests that the results from this project would have a broad application beyond craniofacial dysmorphology.'
Introduzione (Teaser)
Irregularities in facial geometry are a powerful indicator of diseases such as Down's syndrome. European research is refining 3D imaging technologies to detect other disorders where subtle facial anomalies are hardly discernible to the human eye.
Descrizione progetto (Article)
The 'Spectral mesh processing for craniofacial dysmorphology' (http://www.cipa.dcu.ie/face3d/SP_MORPH_Project.htm (SP-MORPH)) project has developed techniques for facial analysis based on spectral decomposition methods. Spectral mesh processing (SMP) has enabled analysis of the whole facial surface in contrast to traditional methods that relied on a reduced set of landmark points.
Data pre-processing involved verification of the composition and quality of the available datasets. The researchers successfully established a robust automated landmarking algorithm. Furthermore, they introduced additional processing that eliminated some of the undesirable artefacts such as holes and disconnected parts. They developed a framework for quantitative evaluation of hole-filling algorithms and generated a realistic dataset of synthetic patches that served as benchmark material.
Normalisation involved application of 'Least Squares Conformal Maps'. Appropriate re-sampling and inverse mappings from 2D to 3D enabled a new representation of the input surfaces in which the whole set is in correspondence.