1. Multi-perspective Panoramas Slides from a talk by Lihi Zelnik-Manor at ICCV’07 3DRR workshop

2. Pictures capture memories

3. Panoramas Registration: Brown & Lowe, ICCV’05 Blending: Burt & Adelson, Trans. Graphics,1983 Visualization: Kopf et al., SIGGRAPH, 2007

4. Bad panorama? Output of Brown & Lowe software

5. No geometrically consistent solution

6. Scientists solution to panoramas: Single center of projection Registration: Brown & Lowe, ICCV’05 Blending: Burt & Adelson, Trans. Graphics,1983 Visualization: Kopf et al., SIGGRAPH, 2007 No 3D!!!

7. From sphere to plane Distortions are unavoidable

8. Distorted panoramas Output of Brown & Lowe software Actual appearance

9. Objectives 1.Better looking panoramas 2.Let the camera move: Any view Natural photographing

10. Stand on the shoulders of giants Cartographers Artists

11. Cartographic projections

12. Common panorama projections θ φ Cylindircal PerspectiveStereographic

13. Global Projections Cylindircal PerspectiveStereographic

14. Learn from the artists Multiple view points De Chirico “Mystery and Melancholy of a Street”, 1914 perspective Sharp discontinuity

15. Renaissance painters solution “School of Athens”, Raffaello Sanzio ~1510 Give a separate treatment to different parts of the scene!!

16. Personalized projections “School of Athens”, Raffaello Sanzio ~1510 Give a separate treatment to different parts of the scene!!

17. Multiple planes of projection Sharp discontinuities can often be well hidden

18. Our multi-view result Single view

19. Our multi-view result Single view

20. Our multi-view result Single view

21. Applying personalized projections Foreground Input images Background panorama

22. Single view Our multi-view result

23. Single view Our multi-view result

24. Objectives - revisited 1.Better looking panoramas 2.Let the camera move: Any view Natural photographing Multiple views can live together

25. Multi-view compositions David Hockney, Place Furstenberg, (1985) 3D!!

26. Melissa Slemin, Place Furstenberg, 2003 Why multi-view? Multiple viewpointsSingle viewpoint David Hockney, Place Furstenberg, 1985

27. Multi-view panoramas Single viewMultiview Requires video input Zomet et al. (PAMI’03)

28. Long Imaging Agarwala et al. (SIGGRAPH 2006)

29. Smooth Multi-View Google maps

30. What’s wrong in the picture? Google maps

31. Non-smooth Google maps

32. The Chair David Hockney (1985)

33. Joiners are popular 4,985 photos matching joiners. 4,007 photos matching Hockney. 41 groups about Hockney Thousands of members Flickr statistics (Aug’07):

34. Main goals: Automate joiners Generalize panoramas to general image collections

35. Objectives For Artists: Reduce manual labor Manual: ~ 40min. Fully automatic

36. Objectives For Artists: Reduce manual labor For non-artists: Generate pleasing-to-the-eye joiners

37. Objectives For Artists: Reduce manual labor For non-artists: Generate pleasing-to-the-eye joiners For data exploration: Organize images spatially

38. What’s going on here?

39. A cacti garden

40. Principles

41. Convey topology Correct Incorrect

42. Principles Convey topology A 2D layering of images Blending: blurry Graph-cut: cuts hood Desired joiner

43. Principles Convey topology A 2D layering of images Don’t distort images rotatescaletranslate

44. Principles Convey topology A 2D layering of images Don’t distort images Minimize inconsistencies Good Bad

45. Algorithm

46. Step 1: Feature matching Brown & Lowe, ICCV’03

47. Step 2: Align Large inconsistencies Brown & Lowe, ICCV’03

48. Step 3: Order Reduced inconsistencies

49. Ordering images Try all orders: only for small datasets

50. Ordering images Try all orders: only for small datasets complexity: (m+n)  m = # images n = # overlaps  = # acyclic orders

51. Ordering images Observations: –Typically each image overlaps with only a few others –Many decisions can be taken locally

52. Ordering images Approximate solution: –Solve for each image independently –Iterate over all images

53. Can we do better?

54. Step 4: Improve alignment

55. Iterate Align-Order-Importance

56. Iterative refinement InitialFinal

57. Iterative refinement InitialFinal

58. Iterative refinement InitialFinal

59. What is this?

60. That’s me reading

61. Anza-Borrego

62. Tractor

63. Paolo Uccello, 1436 Art reproduction

64. Paolo Uccello, 1436 Zelnik & Perona, 2006 Art reproduction

65. Single view-point Zelnik & Perona, 2006 Art reproduction

66. Manual by Photographer

67. Our automatic result

68. Failure?

69. GUI

70. The Impossible Bridge

71. Homage to David Hockney

72. Incorrect geometries are possible and fun! Geometry is not enough, we need scene analysis A highly related work: "Scene Collages and Flexible Camera Arrays,” Y. Nomura, L. Zhang and S.K. Nayar, Eurographics Symposium on Rendering, Jun, 2007. Take home

73. Thank You