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Geometric Optimization Problems in Computer Vision

Explore various optimization techniques like Gauss-Newton iteration, Gradient Descent, and Conjugate Gradient in solving geometric problems in computer vision.

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Geometric Optimization Problems in Computer Vision

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  1. Geometric Optimization Problems in Computer Vision

  2. X x1 x2 x3

  3. Computation of the Fundamental Matrix

  4. b Span(A) Ax O

  5. 1D Gauss-Newton (Newton) iteration.

  6. 1D Gauss-Newton (Newton) iteration (failure)

  7. x1 x0 x2 First step minimizes on line. Second step minimizes function in the plane.

  8. X0

  9. Subdivision search

  10. Gradient Descent

  11. Conjugate Gradient

  12. Newton

  13. Levenberg-Marquardt

  14. Gauss-Newton (without line search)

  15. Newton Conjugate gradient Gradient descent Model 1

  16. Conjugate gradient Gauss-Newton Gradient descent Model 2 Levenberg Newton

  17. Conjugate gradient Gauss-Newton Gradient descent Model 3 Levenberg Newton

  18. Conjugate gradient Gauss-Newton Gradient descent Model 4 Levenberg Newton

  19. Conjugate gradient Gauss-Newton Gradient descent Model 5 Levenberg Newton

  20. Conjugate gradient Gauss-Newton Gradient descent Model 6 Levenberg Newton

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