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Fundamental matrix 
2014/11/28 
ked
Outline 
 Two-view geometry 
 Fundamental matrix 
 Computation 
 Applications
Outline 
 Two-view geometry 
 Fundamental matrix 
 Computation 
 Applications
c c’
c c’
Baseline
Baseline
Epilolar line 
Baseline
Outline 
 Two-view geometry 
 Fundamental matrix 
 Computation 
 Applications
Relate to intrinsic and extrinsic matrix 
Fundamental matrix F: xTFx’ = 0 
F includes intrinsic and extrinsic matrix
 Fundamental matrix
Homogeneous coord.
Outline 
 Two-view geometry 
 Fundamental matrix 
 Computation 
 Applications
Results
Normalization
Outline 
 Two-view geometry 
 Fundamental matrix 
 Computation 
 Applications
Applications 
 Image stitching 
 Structure from motion 
 Stereo reconstruction
Applications 
 Image stitching 
 Structure from motion 
 Stereo reconstruction
Applications 
 Image stitching 
 Structure from motion 
 Chapter 17, structure from motion 
 Stereo reconstruction
Applications 
 Image stitching 
 Structure from motion 
 Chapter 17, structure from motion 
 Stereo reconstruction 
 Chapter 18, stereo
Thx.

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Fundamental matrix

Editor's Notes

  1. 給定兩台camera,找到相對的pixel
  2. 給予對應點,得知camera的相對位置
  3. 給定camera與相對pixel,求取這些點在空間中的位置
  4. 我們從第一個問題開始,用一個系統化的方式來回答這些問題
  5. 第一個問題就是, 給定相機c和c’,相機c的image plane上的一點x,在c’上會變成什麼樣子
  6. 這一點在真實世界中的可能位置,會是一條直線, 這條直線在c的投影是一個點;在c’的投影則是一條直線
  7. C、c’和x的幾何關係,稱為epipolar geometry
  8. 其中,兩個camera center的連線,稱之為baseline
  9. C、c’和X所構成的平面稱之為epipolar plane
  10. Epipolar plane和c’的image plane 的intersection稱之為epipolar line
  11. 根據定義,所有的epipolar plane都會通過baseline, 而所有的epipolar plane會相交於e和e’
  12. E和e’稱為epipole Epipole就是, baseline和image plane的intersection, Camera center在image plane的projection,
  13. Epipolar line與camera之間的關係 跟camera的夾角有關
  14. Camera越平行,epipolar line越水平
  15. 接著是第二個問題, 給定一堆對應點,能知道camera的相對位置嗎
  16. 這個問題關係到intrinsic和extrinsic matrix 系統性的解法是用一個fundamental matrix描述他, 這個fundamental matrix包含了intrinsic matrix和extrinsic matrix, 使得兩個對應點與他的乘積為0
  17. Intrinsic & extrinsic
  18. 以下要說明fundamental matrix
  19. 要計算fundamental matrix, 常見的說法是,先對齊extrinsic matrix,再計算intrinsic matrix 假設intrinsic matrix是identity,p與p’是x的projection
  20. 兩邊同乘ptt後, 可得到ptEp’ = 0
  21. E稱為essential matrix, 就是第二的問題的解答
  22. 對齊extrinsic matrix後, 再加入intrinsic matrix,就可以得到fundamental matrix Fundamental matrix跟c與c’的intrinsic matrix有關
  23. Fundamental matrix有幾個特性
  24. 首先 ,他rank是2 這是因為s的關係,s對稱而且diagonal為0 另外就是,degrees of freedom是7
  25. 對稱性, 如果f是p到p’的fundamental matrix, 那麼ft就是p’到p的fundamental matrix
  26. Pixel position與f的乘積是epipolar line
  27. 有幾個方法可以求取fundamental matrix, 其中一個是八點法 因為fundamental是線性矩陣, 所以可以用最小平方法來求解
  28. 因為fundamental matrix的rank是2, 所以解出來的F還要把它做svd分解,只保留前兩大的eigen value
  29. 值得注意的是,magnitude會影響計算的準度
  30. 所以先做一個normalization很重要
  31. Intersection: epipole: projection of camera center  wrong
  32. 流程
  33. 8 point algorithm要搭配ransac的方法
  34. Fundamental matrix的可能應用有以下幾項, 但是要特別強調的是,image stitching是有條件限制的,並不是所有情況都成立
  35. Stitching是根據對應點將image做warping,然後再blend起來
  36. 這麼做要正確,必須是這兩個條件其中之一 Camera center一樣 或 投影的物體在同一個平面上
  37. 如果camera center相同, Blending影像不會有問題
  38. 但是camera center如果不一樣, cameraA的一個點, 會對應到cameraB的多個點 在blend時, 就會有問題