1. Segmentation and Perceptual Grouping Kaniza (Introduction to Computer Vision, 11.1.04)

6. The image of this cube contradicts the optical image

11. Perceptual Organization Atomism, reductionism: –Perception is a process of decomposing an image into its parts. –The whole is equal to the sum of its parts. Gestalt (Wertheimer, Köhler, Koffka 1912) –The whole is larger than the sum of its parts.

12. Gestalt: apparent motion

14. Gestalt Principles Proximity

15. Gestalt Principles Proximity Similarity

16. Gestalt Principles Proximity Similarity Proximity Similarity Continuity

17. Gestalt Principles ClosureProximity Similarity Continuity

18. Gestalt Principles Proximity Similarity Continuity Closure Common Fate

19. Gestalt Principles Proximity Similarity Continuity Closure Common Fate Simplicity Closure Common Fate

20. Mona Lisa

23. Smooth Completion Isotropic Smoothness Minimal curvature Extensibility Elastica:

24. Elastica Scale invariant (Weiss, Bruckstein & Netravali) Approximation (Sharon, Brandt & Basri)

25. (Sharon, Brandt & Basri)

26. Hough Transform

28. Curve Salience

29. Saliency Network Encourage Length Low curvature Closure (Shashua & Ullman)

30. Saliency Network (Shashua & Ullman)

31. Tensor Voting Every edge element votes to all its circular edge completions Vote attenuates with distance: e -αd Vote attenuates with curvature: e -βk Determine salience at every point using principal moments (Guy & Medioni)

32. Tensor Voting (Guy & Medioni)

33. Stochastic Completion Field Random walk: In addition, a particle may die with probability: (Mumford; Williams & Jacobs)

34. Stochastic Completion Fields Most probable path: with (Mumford; Williams & Jacobs)

35. Stochastic Completion Fields (Mumford; Williams & Jacobs)

36. Stochastic Completion Fields (Mumford; Williams & Jacobs)

37. Stochastic Completion Fields (Mumford; Williams & Jacobs)

38. Shortest Path (Hu, Sakoda & Pavlidis)

39. Snakes Given a curve Г(s)=(x(s),y(s)), define: (Kass, Witkin & Terzopolous)

40. Snakes: Curve Evolution

42. Thresholding

43. Histogram

44. Thresholding

45. 125 156 99

46. Image Segmentation

47. Camouflage

53. Minimum Cut (Wu & Leahy)

54. Texture Examples

55. Filter Bank (Malik & Perona)

56. Normalized Cuts (Malik et al.)

57. Segmentation by Weighted Aggregation A multiscale algorithm: Optimizes a global measure Returns a full hierarchy of segments Linear complexity Combines multiscale measurements: –Texture –Boundary integrity (Galun, Sharon, Brandt & Basri)

58. Segmentation by Weighted Aggregation (Galun, Sharon, Brandt & Basri)

59. Leopards

60. And More…

61. Malik’s Ncuts