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3D Human Body Pose Estimation using GP-LVM

3D Human Body Pose Estimation using GP-LVM. Moin Nabi Computer Vision Group Institute for Research in Fundamental Sciences (IPM). Introduction to Human Pose Estimation. Articulated pose estimation from single-view monocular image(s). Application of Human Pose Estimation.

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3D Human Body Pose Estimation using GP-LVM

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  1. 3D Human Body Pose Estimation using GP-LVM Moin Nabi Computer Vision Group Institute for Research in Fundamental Sciences (IPM)

  2. Introduction to Human Pose Estimation Articulated pose estimation from single-view monocular image(s)

  3. Application of Human Pose Estimation ■ Entertainment: Animation, Games ■ Security: Surveillance ■ Understanding: Gesture/Activity recognition

  4. Difficulties of Human Pose estimation ■ Appearance/size/shape of people can vary dramatically ■ The bones and joints are observable indirectly (obstructed by clothing) ■ Occlusions ■ High dimensionality of the state space ■ Lose of depth information in 2D image projections

  5. Difficulties of Human Pose estimation ■Challenging Human Motion

  6. Problem Backgrounds ■ Pose Estimation From Monocular Image Goal: Reliable 3D Human Pose Estimation from single-camera input

  7. Gaussian process

  8. Gaussian process

  9. Gaussian process

  10. Gaussian process

  11. Gaussian process a 5x5 covariance matrix and a 3-d input vector was used to calculate the 2-d output mean vector and the corresponding variances

  12. Gaussian process Use for Regression

  13. Linear Dimension Reduction

  14. Linear Dimension Reduction Find the best latent inputs by maximizing the marginal likelihood under the constraint that all visible variables must share the same latent values.

  15. Linear Dimension Reduction Find the best latent inputs by maximizing the marginal likelihood under the constraint that all visible variables must share the same latent values.

  16. Linear Dimension Reduction

  17. Linear Dimension Reduction

  18. Linear Dimension Reduction

  19. Gaussian process

  20. Nonlinear Dimension Reduction

  21. Nonlinear Dimension Reduction

  22. Nonlinear Dimension Reduction

  23. Nonlinear Dimension Reduction

  24. Nonlinear Dimension Reduction

  25. Nonlinear Dimension Reduction

  26. Human Pose Estimationusing GP-LVM Image -> Pose In Latent Space

  27. Human Pose Estimationusing GP-LVM Motion capture example, representing 102-D data in 2-D

  28. Human Pose Estimationusing GP-LVM

  29. Result

  30. Result

  31. Pose from Action

  32. Pose from Action Thank You

  33. Future Work Different Action has Different shape in latent space Guess Action from shape of model in latent space

  34. Thank You

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