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# Introduction to homography

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### Introduction to homography

1. 1. Introduction to Homography 2010.01.19
2. 2. Coordinate System view coordinate system object coordinate system x y z world coordinate system
3. 3. History P->G: 以 E 為眼點從平面 G 到平面 W 的 透視對應
4. 4. Outline <ul><li>Projective Geometry </li></ul><ul><li>Projective Transformation </li></ul><ul><li>Estimation </li></ul><ul><ul><li>Document Perspective Distortion </li></ul></ul><ul><ul><li>Direct Linear Transform (DLT) Algorithm </li></ul></ul><ul><li>OpenCV Implementation </li></ul>
5. 5. Homo. representation (1) <ul><li>Lines </li></ul><ul><li>This equivalence relationship is known as a homogeneous vector </li></ul>representative
6. 6. Homo. representation (2) <ul><li>Points </li></ul>Homo. representation
7. 7. Degree of freedom (DoF) <ul><li>Point </li></ul><ul><li>Line </li></ul>
8. 8. <ul><li>2 lines </li></ul><ul><li>Assume </li></ul>Intersection of lines (1)
9. 9. Intersection of lines (2) <ul><li>Ex: determining the intersection of the lines x = 1 and y = 1 </li></ul>y = 1 x = 1
10. 10. Line joining points <ul><li>The line passing through two points x and x’ </li></ul><ul><li>Assume </li></ul>
11. 11. Line at infinity (1) <ul><li>Consider 2 lines </li></ul><ul><li>Intersection </li></ul>
12. 12. Line at infinity (2) <ul><li>Inhomogeneous representation </li></ul><ul><li>No sense ! Suggest the point has infinitely large coordinates </li></ul>Homogeneous coordinates (x, y, 0) T do not correspond to any finite point in R 2
13. 13. Line at infinity (3) <ul><li>Ex: intersection point of 2 lines x=1 and x=2 </li></ul>The point at infinity in the direction of the y-axis
14. 14. Line at infinity (4) <ul><li>Projective Space P 2 : augment R 2 by adding points with last coordinate x 3 = 0 to all homogeneous 3-vectors </li></ul><ul><li>The points with last coordinate x 3 = 0 are known as ideal points , or points at infinity </li></ul><ul><li>The set of all ideal points may be written (x 1 ,x 2 , 0) T . The set lies on a single line, the line at infinity , denoted by the vector (0,0,1) T => (x 1 ,x 2 ,0)(0,0,1) T =0 </li></ul>
15. 15. Concept of points at infinity <ul><li>Simplify the intersection properties of points and lines </li></ul><ul><li>In P 2 , one may state without qualification (not true in the R 2 ) </li></ul><ul><ul><li>2 distinct lines meet in a single point </li></ul></ul><ul><ul><li>2 distinct points lie on a single line </li></ul></ul>
16. 16. A model for the projective plane Points and Lines of P 2 are represented by Rays and Planes , respectively, through the origin in R 3 Lines lying in the x 1 x 2 -plane represent ideal points , and the x 1 x 2 -plane represents l ∞
17. 17. Outline <ul><li>Projective Geometry </li></ul><ul><li>Projective Transformation </li></ul><ul><li>Estimation </li></ul><ul><ul><li>Document Perspective Distortion </li></ul></ul><ul><ul><li>Direct Linear Transform (DLT) Algorithm </li></ul></ul><ul><li>OpenCV Implementation </li></ul>
18. 18. Mapping between planes
19. 19. Definition (1) <ul><li>A projectivity is an invertible mapping h from P 2 to itself such that 3 points x 1 , x 2 and x 3 lie on the same line if and only if h(x 1 ) , h(x 2 ) and h(x 3 ) do </li></ul><ul><li>Synonymous </li></ul><ul><ul><li>Collineation </li></ul></ul><ul><ul><li>Homography </li></ul></ul>
20. 20. Definition (2) <ul><li>A mapping h from P 2 to P 2 </li></ul><ul><li>There exists a non-singular 3 x 3 matrix H such that for any point in P 2 represented by a vector x it is true that </li></ul>
21. 21. Definition (3) <ul><li>H is a homogeneous matrix , since as in the homogeneous representation of a point, only the ratio of the matrix elements is significant (Dof = 8) </li></ul>
22. 22. A hierarchy of transformations (1)
23. 23. A hierarchy of transformations (2)
24. 24. Outline <ul><li>Projective Geometry </li></ul><ul><li>Projective Transformation </li></ul><ul><li>Estimation </li></ul><ul><ul><li>Document Perspective Distortion </li></ul></ul><ul><ul><li>Direct Linear Transform (DLT) Algorithm </li></ul></ul><ul><li>OpenCV Implementation </li></ul>
25. 25. Document Distortion
26. 26. Correction
27. 27. 2D Homography <ul><li>x i in P 2 x j in P 2 </li></ul><ul><li>In a practical situation, the points x i and x j are points in 2 images (or the same image), each image being considered as a projective plane P 2 </li></ul>
28. 28. DLT Algorithm (1)
29. 29. DLT Algorithm (2) <ul><li>Since each point correspondence provides 2 equations, 4 correspondences are suﬃcient to solve for the 8 degrees of freedom of H </li></ul><ul><li>Use more than 4 correspondences to ensure a more robust solution (The problem then becomes to solve for a vector h that minimizes a suitable cost function ) </li></ul>
30. 30. Outline <ul><li>Projective Geometry </li></ul><ul><li>Projective Transformation </li></ul><ul><li>Estimation </li></ul><ul><ul><li>Document Perspective Distortion </li></ul></ul><ul><ul><li>Direct Linear Transform (DLT) Algorithm </li></ul></ul><ul><li>OpenCV Implementation </li></ul>
31. 31. OpenCV Implementation <ul><li>Mat findHomography ( </li></ul><ul><li>const Mat & srcPoints, </li></ul><ul><li>const Mat & dstPoints, </li></ul><ul><li>int method=0, </li></ul><ul><li>double ransacReprojThreshold=3); </li></ul><ul><li>void warpPerspective ( </li></ul><ul><li>const Mat & src, </li></ul><ul><li>CV_OUT Mat & dst, </li></ul><ul><li>const Mat & M, </li></ul><ul><li>Size dsize, </li></ul><ul><li>int flags=INTER_LINEAR, </li></ul><ul><li>int borderMode=BORDER_CONSTANT, </li></ul><ul><li>const Scalar& borderValue=Scalar()); </li></ul>Homography Estimation Projective Transform
32. 32. Reference <ul><li>Multiple View Geometry in Computer Vision , Cambridge University Press, 2000. </li></ul><ul><li>Projective geometry and homogeneous coordinates [Video] - http://www.youtube.com/watch?v=q3turHmOWq4 </li></ul>