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Establishing Point Correspondence of 3D Faces Via Sparse Facial Deformable Model

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.

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Establishing Point Correspondence of 3D Faces Via Sparse Facial Deformable Model

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  1. Establishing Point Correspondence of 3D Faces Via Sparse Facial Deformable Model

  2. Outline • Introduction • Sparse facial deformable model • Solving Shape constraint by face deformation • Correspondence constraint: patch-based sparse representation • Experiments • Conclusions

  3. 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 correspondencebetween 3D faces. We assume that original 3Dfaces are represented as triangle meshes. Other forms of 3Dfaces can be easily changed to meshes

  4. Introduction

  5. Outline • Introduction • Sparse facial deformable model • Solving Shape constraint by face deformation • Correspondence constraint: patch-based sparse representation • Experiments • Conclusions

  6. Sparse Facial Deformable Model

  7. Outline • Introduction • Sparse facial deformable model • Solving Shape constraint by face deformation • Correspondence constraint: patch-based sparse representation • Experiments • Conclusions

  8. Solving Shape Constraint By Face Deformation

  9. Solving Shape Constraint By Face Deformation

  10. Outline • Introduction • Sparse facial deformable model • Solving Shape constraint by face deformation • Correspondence constraint: patch-based sparse representation • Experiments • Conclusions

  11. Correspondence Constraint: Patch-BasedSparse Representation Sparsity Threshold -linear function -exponential function

  12. Correspondence Constraint: Patch-BasedSparse Representation

  13. Outline • Introduction • Sparse facial deformable model • Solving Shape constraint by face deformation • Correspondence constraint: patch-based sparse representation • Experiments • Conclusions

  14. 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.

  15. Experiments

  16. Experiments

  17. Experiments

  18. Experiments

  19. Experiments

  20. Outline • Introduction • Sparse facial deformable model • Solving Shape constraint by face deformation • Correspondence constraint: patch-based sparse representation • Experiments • Conclusions

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