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Automatic landmark annotation and dense correspondence registration for 3D human facial images
- Source :
- BMC Bioinformatics
- Publication Year :
- 2012
-
Abstract
- Dense surface registration of three-dimensional (3D) human facial images holds great potential for studies of human trait diversity, disease genetics, and forensics. Non-rigid registration is particularly useful for establishing dense anatomical correspondences between faces. 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-based feature recognition following 3D-to-2D data transformation. Second, an efficient thin-plate spline (TPS) protocol is used to establish the dense anatomical correspondence between facial images, under the guidance of the predefined landmarks. We demonstrate that this method is robust and highly accurate, even for different ethnicities. The average face is calculated for individuals of Han Chinese and Uyghur origins. While fully automatic and computationally efficient, this method enables high-throughput analysis of human facial feature variation.<br />33 pages, 6 figures, 1 table
- Subjects :
- FOS: Computer and information sciences
Registration
Computer science
Computer Vision and Pattern Recognition (cs.CV)
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Computer Science - Computer Vision and Pattern Recognition
Biochemistry
Quantitative Biology - Quantitative Methods
Annotation
Imaging, Three-Dimensional
Artificial Intelligence
Structural Biology
Humans
Computer vision
Molecular Biology
Quantitative Methods (q-bio.QM)
ComputingMethodologies_COMPUTERGRAPHICS
Dense correspondence
Landmark
business.industry
Methodology Article
Applied Mathematics
Computational Biology
Facial morphology
3D face
Computer Science Applications
Face
FOS: Biological sciences
Face (geometry)
Landmark localization
Artificial intelligence
business
Software
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- BMC Bioinformatics
- Accession number :
- edsair.doi.dedup.....70d358f4c6be7de2a58b3ee2a2c4710a