{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

lecture4 - EECS 442 Computer vision Camera Calibration...

Info iconThis preview shows pages 1–13. Sign up to view the full content.

View Full Document Right Arrow Icon
EECS 442 – Computer vision Camera Calibration • Review camera parameters • Camera calibration problem • Example Reading: [FP] Chapter 3 [HZ] Chapter 7 Some slides in this lecture are courtesy to Profs. J. Ponce & F-F Li
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Pinhole perspective projection Projective camera f O c f = focal length
Background image of page 2
Pinhole perspective projection x y x c y c C=[u o , v o ] f O c Projective camera f = focal length u o , v o = offset
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
f O c Units: k,l [pixel/m] f [m] [pixel] , α β Non-square pixels Projective camera f = focal length u o , v o = offset non-square pixels , α β
Background image of page 4
x y x c y c C=[u o , v o ] θ f O c Projective camera non-square pixels , f = focal length u o , v o = offset α β θ = skewness
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
f O c Projective camera = 1 z y x 0 1 0 0 0 v 0 0 u cot P o o sin θ β θ α α K has 5 degrees of freedom! P c P’ f = focal length u o , v o = offset non-square pixels , α β θ = skewness
Background image of page 6
f O c Projective camera P c O w i w k w j w R,T [ ] w c P T R P = P’ f = focal length u o , v o = offset non-square pixels , α β θ = skewness R,T = rotation, translation
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
f = focal length u o , v o = offset non-square pixels , α β f O c Projective camera P O w i w k w j w R,T w P M P = [ ] w P T R K = Internal parameters External parameters θ = skewness R,T = rotation, translation P’
Background image of page 8
Goal of calibration w P M P = [ ] w P T R K = Internal parameters External parameters Estimate intrinsic and extrinsic parameters from 1 or multiple images
Background image of page 9

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Goal of calibration w P M P = [ ] w P T R K = Estimate intrinsic and extrinsic parameters from 1 or multiple images Note: To simplify notation let P = P w = 1 0 0 v 0 u cot K o o sin θ β θ α α = T 3 T 2 T 1 R r r r = z y x t t t T
Background image of page 10
Calibration Problem •P 1 … P n with known positions in [O w ,i w ,j w ,k w ] •p 1 , … p n known positions in the image Goal : compute intrinsic and extrinsic parameters j Calibration rig
Background image of page 11

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Calibration Problem
Background image of page 12
Image of page 13
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}