An Automatic 3D Facial Landmarking Algorithm Using 2D Gabor Wavelets.
IEEE Trans Image Process
; 25(2): 580-8, 2016 Feb.
Article
en En
| MEDLINE
| ID: mdl-26540684
In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend an established 2D landmarking method for simultaneous evaluation of these data. The method is validated by performing landmarking experiments on two data sets using 21 landmarks and compared with an active shape model implementation. On average, landmarking error for our method was 1.9 mm, whereas the active shape model resulted in an average landmarking error of 2.3 mm. A second study investigating facial shape heritability in related individuals concludes that automatic landmarking is on par with manual landmarking for some landmarks. Our algorithm can be trained in 30 min to automatically landmark 3D facial data sets of any size, and allows for fast and robust landmarking of 3D faces.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Imagenología Tridimensional
/
Cara
/
Análisis de Ondículas
/
Puntos Anatómicos de Referencia
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
IEEE Trans Image Process
Asunto de la revista:
INFORMATICA MEDICA
Año:
2016
Tipo del documento:
Article
Pais de publicación:
Estados Unidos