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Stereo matching
2015/01/23
ked
Outline
 Why stereo
 Depth from disparity
 Basic algorithm
 Segment-based approach
Outline
 Why stereo
 Depth from disparity
 Basic algorithm
 Segment-based approach
Stereo matching
Stereo matching
Stereo matching
Frederic Devernay
Height field image
Stereo matching
Stereo matching
Stereo matching
Outline
 Why stereo
 Depth from disparity
 Basic algorithm
 Segment-based approach
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Depth from shading
Depth from focus
Depth from texture
Outline
 Why stereo
 Depth from disparity
 Basic algorithm
 Segment-based approach
Stereo matching
Stereo matching
Use for
Stereo matching
Stereo matching
Why
Stereo matching
Loop & Zhang 1999





Loop & Zhang 1999

Loop & Zhang 1999

Align epipolar lines
Loop & Zhang 1999

Reduce horizontal distortion
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Outline
 Introduction
 Image rectification
 Basic algorithm
 Segment-based approach
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Stereo matching
Global energy minimization
Thx.

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Stereo matching

Editor's Notes

  1. 由兩張甚至是多張影像,去推算物體的三維形狀
  2. 先來看它可能的應用
  3. 三維模型的重建 (原投影片名字寫錯)
  4. 關於model,比較常見的方法是產生depth map, 所謂的depth map,就是height field image,它在image的每個pixel紀錄三維空間的高度
  5. 有了depth map後,就能內插出從不同角度看到的結果
  6. 有了depth image後,就能以image based或model based的方法,產生vfx
  7. 而我覺得最實用的地方, 我覺得是機器移動的控制, 目前流行的智慧車輛,有些就是用這個方法來做
  8. 要如何從兩張以上的image,得到depth map
  9. Stereo reconstruction與人眼的立體視覺相似
  10. 看物體的時候,人的眼睛會旋轉,然後在物體上產生焦點
  11. 而焦點之外的其他地方,則會在視網膜上產生偏差, 就是這個偏差,讓人眼視覺有了立體感,稱為disparity
  12. Disparity的表現有幾種方式,其中一種是在image plane上的位移
  13. 另一種則是計算視角的差異, 不過所表示的是同一回事 資訊界喜歡用前一種,心理學上則偏好後者
  14. Stereo reconstruction的數學推導跟人眼視覺一樣, 用相似三角形的原理,可以由baseline、focal length、和disparity得到depth
  15. 這是depth from disparity的例子
  16. 步驟,主要是三步
  17. 第一步之前講過,最主要的是,要得到正確的depth,一定要求得focal length和baseline 另外求取fundamental matrix,以便後續的rectify image
  18. 第二步是影像轉正,它使得後續的計算比較方便
  19. 把epipolar拉到無限遠
  20. 排名很前面的舊方法
  21. 介紹這篇