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Model-Based Stereo with Occlusions

Model-Based Stereo with Occlusions. Fabiano Romeiro and Todd Zickler. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A A A A A. Introduction. Varying illumination. Varying pose. Occlusions. Varying expressions. Introduction.

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Model-Based Stereo with Occlusions

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  1. Model-Based Stereo with Occlusions Fabiano Romeiro and Todd Zickler TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAAAAAA

  2. Introduction Varying illumination Varying pose Occlusions Varying expressions

  3. Introduction Past Work: Image-based For example: Eigenfaces [Turk and Pentland, 1991] Fisherfaces [Belhumeur et al, 1997]

  4. 3D Morphable Models (3DMMs) 2D+3D AAMs 2D AAMs [Cootes et al, 1998; Baker et al, 2004; Mathews et al, 2004; Gross et al, 2006] [Xiao et al, 2004] [Blanz et al, 1999; Blanz et al, 2003; Blanz et al, 2005; Smet et al, 2006] Introduction Past Work: Model-based

  5. 3D Morphable Models (3DMMs) Pros • - Self-occlusion handled by model itself • - Allows direct modeling of illumination Cons - Difficult and expensive fitting process [Blanz et al, 1999; Blanz et al, 2003; Blanz et al, 2005; Smet et al, 2006] Introduction Past Work: 3DMMs

  6. - Stereo based cost [Fransens et al, 2005] • Stereo fitting with both shape and texture • →Robust to foreign-body occlusions Introduction Past Work: Stereo 3DMMs - Texture model not needed Our work • → Improved Accuracy

  7. Outline • 3DMM Background • Joint Shape and Texture Stereo Fitting • Handling Occlusions • Conclusions

  8. Basis for shape - Basis for texture Background 3DMMs Vectorization of laser scans: PCA performed: [Blanz and Vetter, 1999]

  9. [Blanz and Vetter, 1999] Background 3DMMs Representation of face shape and texture: Prior probabilities on the coefficients:

  10. Stereo Match

  11. Texture Match

  12. Joint Shape and Texture Stereo Fitting of 3DMMs

  13. Robust Stereo Fitting of 3DMMs

  14. Optimization Procedure Initial fit - Fit Shape, Pose to minimize reprojection error on selected feature points - Rough initial estimates of Shape and Pose Optimization procedure 4 experiments Stereo and texture Stereo Robust Stereo and texture Robust Stereo

  15. Results First 2 experiments: Stereo and Texture vs. Stereo 480 recovered shape models (60 individuals, 8 poses) K.U. Leuven Stereo face database [Fransens et al, 2005]

  16. Results Qualitative Results Stereo and Texture Stereo

  17. Results Qualitative Results Stereo+texture Stereo

  18. Results Quantitative Results

  19. Results Under Occlusions Half-Occlusion Full Occlusion near Full-Occlusion far

  20. Robust Stereo Robust S+T Results Under Occlusions Input Robust Stereo Robust S+T Shape Estimate Occlusion Map

  21. Conclusions Robust stereo fitting of 3DMMs - Uses both stereo constraint, texture information • Increased accuracy of fit - Ability to handle occlusions Future Work - More sophisticated stereo matching term - Different feature spaces - Break model into segments respecting occlusion boundaries

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