Automatic landmark annotation and dense correspondence registration for 3D human facial images.

ABSTRACT:

Background

Traditional anthropometric studies of human face rely on manual measurements of simple features, which are labor intensive and lack of full comprehensive inference. Dense surface registration of three-dimensional (3D) human facial images holds great potential for high throughput quantitative analyses of complex facial traits. However there is a lack of automatic high density registration method for 3D faical images. Furthermore, current approaches of landmark recognition require further improvement in accuracy to support anthropometric applications.

Result

Here we describe a novel non-rigid registration method for fully automatic 3D facial image mapping. This method comprises two steps: first, seventeen facial landmarks are automatically annotated, mainly via PCA-

SUBMITTER: Guo J 

PROVIDER: S-EPMC3724574 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature