The structure of the movement, the restoration of a 3D point cloud when setting the correspondence of two image points

Use case


  • The object rotates around its center with variable speed.
  • A fixed camera looks at an object
  • Given the correspondence of two-dimensional images, a 3D point cloud
  • As the object rotates, therefore, another part of it is visible on it, and thus different points and correspondences are detected.


Scene


  and. N images
  b. N-1 pairs of images
  c. N-1 2D point correspondence (two arrays of two-dimensional points)


Implementation


For each of the (N-1) two-dimensional correspondence points

  • Calculate relative camera pose
  • Triangulate to get 3D glasses
  • For each 2 arrays of 3D points, derive a correspondence using the two-dimensional correspondence given in [c]
  • 3D- @[3], , /


:


A (N-2) 3D-, , ( )


, :


, , .
   , A. Camera:
      ( ).   . , , , , ..
  . [B], 3D- [A] Cameras Translations
               

  D. ( @[4])
       
    Pose), .

?

+4
1

. . , , , .

intereset. SURF SIFT - . 15 °, , USURF, , SURF ( SURF). Optical Flow OpenCV, , . , .

. , (, - - )? , . , , . , , .

. - . , . , . , , . , , , .

, . . , , , RANSAC . , , , Intereset .

, , - , . 2D 3D- . PerspectivenPoint Camera Pose Estimation (PnP).

. . , :

Live Metric 3D-

+3

Source: https://habr.com/ru/post/1540248/


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