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Motion Capture Using Joint Skeleton Tracking and Surface Estimation

Motion Capture Using Joint Skeleton Tracking and Surface Estimation. Juergen Gall Carsten Stoll Edilson de Aguiar Christian Theobalt Bodo Rosenhahn Hans-Peter Seide CVPR 2009. Outline. Introduction Skeleton-based Pose Estimation Experiment Conclusion . Local Optimization.

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Motion Capture Using Joint Skeleton Tracking and Surface Estimation

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  1. Motion Capture Using Joint Skeleton Tracking and Surface Estimation JuergenGall CarstenStoll Edilson de Aguiar Christian Theobalt BodoRosenhahn Hans-Peter Seide CVPR 2009

  2. Outline • Introduction • Skeleton-based Pose Estimation • Experiment • Conclusion

  3. Local Optimization 3D - 2D correspondences (V , x) x can be represented as Plucker line L = (n , m) , the error is given by 

  4. Local Optimization Equation (1) ,(2) solved by Taylor approximation Limb-specific energy

  5. Global Optimization • Reference :

  6. Surface Estimation • Laplacian deformation framework

  7. Experiments

  8. Conclusion • Presented an approach that recovers skeleton pose and surface motion fully-automatically from multi-view video sequence. • Introduced a novel optimization scheme for skeleton-based pose estimation. • It allows subjects wearing wide apparel.

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