3D photography

1. 3D photography Marc Pollefeys Fall 2004 / Comp 290-089 Tue & Thu 9:30-10:45 http://www.unc.edu/courses/2004fall/comp/290/089/

2. Material On-line “shape-from-video” tutorial: http://www.cs.unc.edu/~marc/tutorial.pdf http://www.cs.unc.edu/~marc/tutorial/ Slides, notes, papers and references see course webpage (later): http://www.unc.edu/courses/2004fall/comp/290/089/

3. Learning approach • In the first part of the class the main 3D photography approaches will be covered in detail. • A few programming assignments will be given to support this. • In the second part of the class students will present and discuss relevant papers to explore the state-of-the-art. • Small groups of students or individual students will build 3D photography systems as course projects. Grade distribution • Assignments: 25% • Paper presentation and class participation: 25% • Course project: 50%

4. Papers and discussion • Will cover recent state of the art Each student will present paper, discussion List on website (later), own suggestions Some shared class sessions with Leonard’s Data-Driven Modeling in Computer Graphics

5. Course project: Build your own 3D scanner!(or something like that) Example: Bouguet ICCV’98 Students can work in group or alone Start thinking of your project today!

6. 3D photography course schedule(tentative)

7. Projective Geometry and Camera model Class 2 points, lines, planes conics and quadrics transformations camera model Read tutorial chapter 2 and 3.1 http://www.unc.edu/courses/2004fall/comp/290/089/

8. Homogeneous coordinates but only 2DOF Inhomogeneous coordinates Homogeneous coordinates Homogeneous representation of 2D points and lines The point x lies on the line l if and only if Note that scale is unimportant for incidence relation equivalence class of vectors, any vector is representative Set of all equivalence classes in R3(0,0,0)T forms P2

9. Line joining two points The line through two points and is Points from lines and vice-versa Intersections of lines The intersection of two lines and is Example Note: with

10. tangent vector normal direction Example Ideal points Line at infinity Ideal points and the line at infinity Intersections of parallel lines Note that in P2 there is no distinction between ideal points and others

11. 3D points and planes Homogeneous representation of 3D points and planes The point X lies on the plane πif and only if The plane πgoes through the point X if and only if

12. (solve as right nullspace of ) Planes from points

13. (solve as right nullspace of ) Points from planes Representing a plane by its span

14. Dual representation Lines Representing a line by its span (4dof) Example: X-axis (Alternative: Plücker representation, details see e.g. H&Z)

15. Points, lines and planes

16. or homogenized or in matrix form with Conics Curve described by 2nd-degree equation in the plane 5DOF:

17. stacking constraints yields Five points define a conic For each point the conic passes through or

18. Tangent lines to conics The line l tangent to C at point x on C is given by l=Cx l x C

19. In general (C full rank): Dual conics A line tangent to the conic C satisfies Dual conics = line conics = conic envelopes

20. Note that for degenerate conics Degenerate conics A conic is degenerate if matrix C is not of full rank e.g. two lines (rank 2) e.g. repeated line (rank 1) Degenerate line conics: 2 points (rank 2), double point (rank1)

21. Quadrics and dual quadrics (Q : 4x4 symmetric matrix) • 9 d.o.f. • in general 9 points define quadric • det Q=0 ↔ degenerate quadric • tangent plane • relation to quadric (non-degenerate)

22. Theorem: A mapping h:P2P2is a projectivity if and only if there exist a non-singular 3x3 matrix H such that for any point in P2 reprented by a vector x it is true that h(x)=Hx Definition: Projective transformation or 8DOF 2D projective transformations Definition: A projectivity is an invertible mapping h from P2 to itself such that three points x1,x2,x3lie on the same line if and only if h(x1),h(x2),h(x3) do. projectivity=collineation=projective transformation=homography

23. Transformation for conics Transformation for dual conics Transformation of 2D points, lines and conics For a point transformation Transformation for lines

24. (eigenvectors H-T =fixed lines) Fixed points and lines (eigenvectors H =fixed points) (1=2 pointwise fixed line)

25. Hierarchy of 2D transformations transformed squares invariants Concurrency, collinearity, order of contact (intersection, tangency, inflection, etc.), cross ratio Projective 8dof Parallellism, ratio of areas, ratio of lengths on parallel lines (e.g midpoints), linear combinations of vectors (centroids). The line at infinity l∞ Affine 6dof Ratios of lengths, angles. The circular points I,J Similarity 4dof Euclidean 3dof lengths, areas.

26. The line at infinity The line at infinity l is a fixed line under a projective transformation H if and only if H is an affinity Note: not fixed pointwise

27. Affine properties from images projection rectification

28. Affine rectification l∞ v1 v2 l1 l3 l2 l4

29. The circular points The circular points I, J are fixed points under the projective transformation H iff H is a similarity

30. l∞ Algebraically, encodes orthogonal directions The circular points “circular points”

31. The dual conic is fixed conic under the projective transformation H iff H is a similarity Note: has 4DOF l∞ is the nullvector Conic dual to the circular points l∞

32. Projective: (orthogonal) Angles Euclidean:

33. Transformation of 3D points, planes and quadrics For a point transformation (cfr. 2D equivalent) Transformation for lines Transformation for conics Transformation for dual conics

34. Hierarchy of 3D transformations Projective 15dof Intersection and tangency Parallellism of planes, Volume ratios, centroids, The plane at infinity π∞ Affine 12dof Similarity 7dof Angles, ratios of length The absolute conic Ω∞ Euclidean 6dof Volume

35. The plane at infinity The plane at infinity π is a fixed plane under a projective transformation H iff H is an affinity • canical position • contains directions • two planes are parallel  line of intersection in π∞ • line // line (or plane)  point of intersection in π∞

36. The absolute conic The absolute conic Ω∞ is a (point) conic on π. In a metric frame: or conic for directions: (with no real points) The absolute conic Ω∞ is a fixed conic under the projective transformation H iff H is a similarity • Ω∞is only fixed as a set • Circle intersect Ω∞ in two circular points • Spheres intersect π∞ in Ω∞

37. The absolute conic Euclidean: Projective: (orthogonality=conjugacy) normal plane

38. The absolute dual quadric The absolute conic Ω*∞ is a fixed conic under the projective transformation H iff H is a similarity • 8 dof • plane at infinity π∞ is the nullvector of Ω∞ • Angles:

39. Camera model Relation between pixels and rays in space ?

40. Pinhole camera

41. Pinhole camera model linear projection in homogeneous coordinates!

42. Pinhole camera model

43. Principal point offset principal point

44. Principal point offset calibration matrix

45. Camera rotation and translation ~

46. CCD camera

47. non-singular General projective camera 11 dof (5+3+3) intrinsic camera parameters extrinsic camera parameters

48. Radial distortion • Due to spherical lenses (cheap) • Model: R R straight lines are not straight anymore http://foto.hut.fi/opetus/260/luennot/11/atkinson_6-11_radial_distortion_zoom_lenses.jpg

49. Camera model Relation between pixels and rays in space ?

50. Projector model Relation between pixels and rays in space (dual of camera) (main geometric difference is vertical principal point offset to reduce keystone effect) ?