establishing point correspondence of 3d faces via sparse facial deformable model
DESCRIPTION
Establishing Point Correspondence of 3D Faces Via Sparse Facial Deformable Model. Outline. Introduction Sparse facial deformable model Solving Shape constraint by face deformation Correspondence constraint: patch-based sparse representation Experiments Conclusions. Introduction. - PowerPoint PPT PresentationTRANSCRIPT
Establishing Point Correspondence of 3D Faces Via Sparse Facial Deformable Model
Outline
IntroductionSparse facial deformable model Solving Shape constraint by face deformationCorrespondence constraint: patch-based
sparse representationExperiments Conclusions
Introduction
Recent progresses in 3D digital acquisition techniques allow 3D data to be accurately captured in real time. This otivates extensive researches on 3D data in computer vision and computer graphics communities
This paper aims at building an anthropometric dense correspondence between 3D faces. We assume that original 3D faces are represented as triangle meshes. Other forms of 3D faces can be easily changed to meshes
Introduction
Outline
IntroductionSparse facial deformable model Solving Shape constraint by face deformationCorrespondence constraint: patch-based
sparse representationExperiments Conclusions
Sparse Facial Deformable Model
Outline
IntroductionSparse facial deformable model Solving Shape constraint by face deformationCorrespondence constraint: patch-based
sparse representationExperiments Conclusions
Solving Shape Constraint By Face Deformation
Solving Shape Constraint By Face Deformation
Outline
IntroductionSparse facial deformable model Solving Shape constraint by face deformationCorrespondence constraint: patch-based
sparse representationExperiments Conclusions
Correspondence Constraint: Patch-BasedSparse Representation
Sparsity Threshold
-linear function
-exponential function
Correspondence Constraint: Patch-BasedSparse Representation
Outline
IntroductionSparse facial deformable model Solving Shape constraint by face deformationCorrespondence constraint: patch-based
sparse representationExperiments Conclusions
Experiments
Rn computes the average distance between the vertices on M’ and their nearest vertices on M, which exhibits the reconstruction accuracy.Rl f computes the average distance between the vertices on M’ and their corresponding vertices on Ml f , which implies the accuracy of overall correspondence.Rl computes the average distance between the landmarks on M and their corresponding landmarks on M’, which shows the accuracy of landmark correspondence.Dl shows the accuracy of the anthropometric correspondence from the view of face structure.
Experiments
Experiments
Experiments
Experiments
Experiments
Outline
IntroductionSparse facial deformable model Solving Shape constraint by face deformationCorrespondence constraint: patch-based
sparse representationExperiments Conclusions