CV2011 Lecture 1. Part 1. Introduction to computer vision
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CV2011 Lecture 1. Part 1. Introduction to computer vision
- 2. 弍舒 亳仆仂仄舒亳磤仂 从 仗仂亟亞仂仂于仍亠仆亳 亳舒亠 仗亳 仗仂亟亟亠亢从亠 Microsoft Research弌舒仆亳舒 从舒 http://courses.graphicon.ru/main/vision 仍亠从仂亠舒弍. 从仂仄仗ﾑ亠仆仂亶 亞舒亳从亳 亳 仄仍亳仄亠亟亳舒舒仆亶 仂亟仆亳从, 从.-仄.仆., 从仂于仂亟亳亠仍 亞仗仗 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳仆仂仆 仂仆亳仆 :
- 3. 弌/从 束于亠亟亠仆亳亠 于 从仂仄仗ﾑ亠仆仂亠 亰亠仆亳亠損 (于亠仆舒)
- 4. 弌/从 束仂仗. 亞仍舒于 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳晛 (仂亠仆)
- 6. 弌/从 束仆舒仍亳亰 亳亰仂弍舒亢亠仆亳亶 亳 于亳亟亠仂損 (亞仂亟), 丿 亊仆亟亠从
- 7. E-mail: ktosh@graphics.cs.msu.ru弍 舒亳亠仆亠仗亳舒仆 1-亞仂 亞仂亟舒 丕舒弍. 从仂仄仗. 亞舒亳从亳 亳 仄仍亳仄亠亟亳舒仗仗舒 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳aachigorin@gmail.com仍亠从舒仆亟 丼亳亞仂亳仆
- 8. 丕亠弍仆亳从亳个仂舒亶, 仂仆 束仂仄仗ﾑ亠仆仂亠 亰亠仆亳亠: 仂于亠仄亠仆仆亶 仗仂亟仂亟損
- 9. R.Szeliski束Computer vision: Algorithm and applications損
- 10. http://research.microsoft.com/en-us/um/people/szeliski/Book/仍舒仆 仍亠从亳亳于亠亟亠仆亳亠 于 从仂仄仗ﾑ亠仆仂亠 亰亠仆亳亠丼仂 仂 舒从仂亠仂亠仄 仂 仍仂亢仆仂仂亳 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳碻仂于亠仄亠仆仆亠 亟仂亳亢亠仆亳舒亟舒亳, 亠舒亠仄亠 于 仍舒弍仂舒仂亳亳弍亰仂 仗仂亞舒仄仄 从舒仂仄仗ﾑ亠仆仂亠 亰亠仆亳亠 亳 亰亠仆亳亠 亠仍仂于亠从舒亰仂弍舒亢亠仆亳亠舒仄亠舒 亳 亞仍舒亰丶于亠亳 弍舒仍舒仆 弍亠仍仂亞仂
- 11. 舒亟舒舒 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳仂仆, 仂 亰舒仗亠舒仍亠仆仂 仆舒 亳亰仂弍舒亢亠仆亳亳 于亳亟亳仄仂仄仗ﾑ亠 于亳亟亳Source: S. Narasimhan
- 12. 舒亟舒舒 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳昮To see means to know what is where by looking損David Marr, Vision, 1982仂仆, 仂 亰舒仗亠舒仍亠仆仂 仆舒 亳亰仂弍舒亢亠仆亳亳丼仂 仂 于 亟亠亶于亳亠仍仆仂亳 仂弍仂亰仆舒舒亠?亠仆亳亠 - 亳仂仆亳从 亠仄舒仆亳亠从仂亶 亳仆仂仄舒亳亳 仂 仄亳亠亠仆亳亠 - 亳仂仆亳从 仄亠亳亠从仂亶 亳仆仂仄舒亳亳 仂 亠仄亠仆仂仄 仄亳亠
- 13. 弌亠仄舒仆亳亠从舒 亳仆仂仄舒亳寍際滷 credit: Fei-Fei, Fergus & Torralba
- 15. 亞仂仂亟
- 16. 仍亳仆仂亠 亟于亳亢亠仆亳亠
- 17. 亠从亳仆, 亳舒亶
- 18. 仍. 丐礌舒仆仄仆際際滷 10slide credit: Fei-Fei, Fergus & Torralba
- 19. 仂亳从 亳 仍仂从舒仍亳亰舒亳 仂弍亠从仂于亟舒仆亳亠个仍舒亞亳仂丐亠从于仂弍于仂弍際際滷 11際際滷 credit: Fei-Fei, Fergus & Torralba
- 21. 舒亠于亠仆仆舒 亳仆仂仄舒亳仂仍弍仂亠仆舒从仍仂仆仆舒亠亠 仗舒于舒 仆舒仍亠于仂亠亢亠从亳亶, 亟于亳亢亠舒仂亠从亳亶, 亟于亳亢亠亠从亳亶, 亟于亳亢亠磪仂亳亰仂仆舒仍仆亶際際滷 13slide credit: Fei-Fei, Fergus & Torralba
- 22. 亠亳亠从舒 亳仆仂仄舒亳仂亟亠仍亳仂于舒仆亳亠 仗仂 仗仂仍亰仂于舒亠仍从亳仄 仆亳仄从舒仄弌亠亠仂 亠从仂仆从亳碻从舒 亳亰 亟于亳亢亠仆亳NASA Mars RoverGoesele et al.Pollefeys et al.際際滷: Svetlana Lazebnik
- 24. 亠仆亳亠 仗亳仆亠 仆舒亰于舒仆亳弍舒弍仂从舒 亳亰仂弍舒亢亠仆亳亶 (Image processing)舒 于仂亟亠 亳 于仂亟亠 亳亰仂弍舒亢亠仆亳亠仆舒仍亳亰 亳亰仂弍舒亢亠仆亳亶 (Image analysis)个仂从亳亠 仆舒 舒弍仂亠 2D 亳亰仂弍舒亢亠仆亳礆亳舒仗仂亰仆舒于舒仆亳亠 仂弍舒亰仂于 (Pattern recognition)舒仗仂亰仆舒于舒仆亳亠, 仂弍亠仆亳亠 仆舒 舒弍舒从仆 亳仍仂于 于亠仍亳亳仆舒, 仗仂仍亠仆仆 于 仂仄 亳仍亠 亳 亳亰 亳亰仂弍舒亢亠仆亳亶仂仄仗ﾑ亠仆仂亠 亰亠仆亳亠 (弌omputer vision)亰仆舒舒仍仆仂 于仂仂舒仆仂于仍亠仆亳亠 3亟 从 仗仂 2亟 亳亰仂弍舒亢亠仆亳礆, 亠亶舒 亳亠, 从舒从 仗亳仆亳亠 亠亠仆亳亶 仂 亳亰亳亠从亳 仂弍亠从舒, 仂仆仂于于舒 仆舒 亳 亳亰仂弍舒亢亠仆亳个仂仂亞舒仄仄亠亳 (Photogrammetry) 仂亳亠从亳 亳亰仄亠亠仆亳亠 舒仂礌亳亶 仄亠亢亟 仂弍亠从舒仄亳 仗仂 2D 亳亰仂弍舒亢亠仆亳礆舒亳仆仆仂亠 亰亠仆亳亠 (achine vision)弍仆仂 仗仂仆亳仄舒亠 从舒从 亠亠仆亳亠 仗仂仄仍亠仆仆, 仗仂亳亰于仂亟于亠仆仆 亰舒亟舒 (仍仂亢亳仍仂 亳仂亳亠从亳)
- 25. 舒亠仄?仂仍亠亰仆仂 仄仆仂亞仂 仗舒从亳亠从亳 仗亳仄亠仆亠仆亳亶仆亠亠仆仂 仆舒亞仍磲仆仂亠 仗亳仄亠仆亠仆亳亠 仄舒 仄舒亠仄舒亳亠从亳 仄亠仂亟仂于弌仍仂亢仆仂25+% 仄仂亰亞舒 亠仍仂于亠从舒 仂于亠舒亠 亰舒 亰亠仆亳亠束-仗仂仍仆舒晛 亰舒亟舒舒 亠亠仆亳亠 亰舒亟舒亳 亰亠仆亳 仆舒 仂于仆亠 亠仍仂于亠从舒 舒于仆仂亳仍仆仂 亠亠仆亳 亰舒亟舒亳 亳从于亠仆仆仂亞仂 亳仆亠仍仍亠从舒
- 26. 仂亠仄 亰亠仆亳亠 仂 仍仂亢仆仂?
- 27. 丐仂从舒 仆舒弍仍ﾐ莞黍出狐Michelangelo 1475-1564slide credit: Fei-Fei, Fergus & Torralba
- 28. 于亠亠仆亳亠image credit: J. Koenderink
- 29. 舒舒弍際際滷 credit: Fei-Fei, Fergus & Torralba
- 30. 亠仂仄舒亳Xu, Beihong 1943際際滷 credit: Fei-Fei, Fergus & Torralba
- 31. 亠亠从亳亠Magritte, 1957 slide credit: Fei-Fei, Fergus & Torralba
- 32. 舒从亳仂于从舒
- 33. 于亳亢亠仆亳亠
- 34. 仆亳从仍舒仂于舒 亳亰仄亠仆亳于仂際際滷 credit: Fei-Fei, Fergus & Torralba
- 35. 仂仆亠从仂仍亠仆仂弌仍
- 37. 弌仍仂亢仆仂亳 亳仍亳 于仂亰仄仂亢仆仂亳?亰仂弍舒亢亠仆亳亠 亰舒仗于舒亠, 仆仂 亟舒亠 仄仆仂亞仂 仗仂亟从舒亰仂从 舒舒 亰舒亟舒舒 亳仆亠仗亠亳仂于舒 仗仂亟从舒亰从亳Image source: J. Koenderink
- 38. 丶于亠
- 39. 丐亠仆亳 亳 仂于亠亠仆亳亠Source: J. Koenderink
- 40. 弍舒于舒亠仄亠 亠仆亳Source: J. Koenderink
- 41. 仗仗亳仂于从舒Image credit: Arthus-Bertrand (via F. Durand)
- 43. 丐亠从舒
- 44. 丕仗仂磲仂亳于舒仆亳亠 仗仂 亞仍弍亳仆亠Source: J. Koenderink
- 45. 丐仄舒仆 亳 仂从亳仂于从舒
- 46. 亠亰ﾐ斜黍亠仆亳亠 亳亰仆舒舒仍仆仂 仆亠亠从舒 亰舒亟舒舒舒亰仆亠 3D 亠仆 亟舒ﾑ 仂亟仆仂 亳 仂 亢亠 2D 亳亰仂弍舒亢亠仆亳亠亠仂弍仂亟亳仄 舒仗亳仂仆亠 亰仆舒仆亳 仂 从亠 亳 于仂亶于舒 仄亳舒Image source: F. Durand
- 47. 仂亳: 舒仄亠舒-仂弍从舒亳仆亳仗 弍仍 亳亰于亠亠仆 亠亠 亳仂亠仍 (384-322 亟仂 .亅.)Magic Lantern, 1492
- 48. 1525
- 49. 亠于舒 仂仂亞舒亳碻舒仄舒 仗亠于舒 仂仂亞舒亳1825 亞仂亟丐亠弍仂于舒仍舒 8 舒仂于 仗仂磦从亳
- 50. 个仂仂亞舒仄仄亠亳1837 仗亠于亠 仗舒从亳亠从亳 仗亳仄亠仆亳仄亠 仂仂亞舒亳亳1840 束个仂仂亞舒仄仄亠亳 弍亟亠亠 亞亠仂亟亠亰亳亳損
- 51. 亳亟亠仂1888 仗亠于仂亠 从亳仆仂 仆舒 仗仍仆从亠, Louis Le Prince1878 仗亠于舒 从仂仂仆舒 亠仄从舒, Eadweard Muybridge
- 52. 亅仍亠从仂仆仆仂-仍亠于舒 弍从舒(CRT)1885 亳亰仂弍亠亠仆亳亠 弌RT1897 弌RT c 仍仂亠亠仆仆仄 从舒仆仂仄
- 54. 舒仂于亶 亟亳仗仍亠亶 1927 亞仂亟Philo Farnsworth 60-仂仆亶 舒仂于亶 亟亳仗仍亠亶
- 55. Whirlwind, MIT, 1951亠于亶 从仂仄仗ﾑ亠, 仂仂弍舒亢舒ﾑ亳亶 亠从 亳 亞舒亳从 于 亠舒仍仆仂仄 于亠仄亠仆亳 仆舒 仄仂仆亳仂亠丐仂从舒仄亳 从舒, 亰仆舒从仂仄 舒仄仂仍.束弌于亠仂于仂亠 仗亠仂損 亟仍 于亰舒亳仄仂亟亠亶于亳 从舒仆仂仄 (亰舒仗仂 亳仆仂仄舒亳亳 仂弍 仂弍亠从亠)
- 56. 1957 - 1967仆舒仍仂亞仂于亠 仂仗仂舒于亳亠仍亳 亳亰仂弍舒亢亠仆亳亶
- 57. The Boing man, 1960亠于仂亠 从仂仄仗ﾑ亠仆仂亠 亳亰仂弍舒亢亠仆亳亠 亠仍仂于亠从舒
- 58. 舒仂亢亟亠仆亳亠 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳L. G. Roberts, Machine Perception of Three Dimensional Solids, Ph.D. thesis, MIT Department of Electrical Engineering, 19601963.
- 59. Spacewar, MIT, 1961Steve Russell, 200 亠仍仂于亠从仂-仄亠亠于
- 60. SketchPad, MIT, 1963Ivan Sutherland 亟亠仄仂仆亳亠 亳仆亠舒从亳于仆亶 亞舒亳亠从亳亶 亠亟舒从仂 SketchPad
- 61. CAD, IBM + GM, 1964亠于舒 弌AD-亳亠仄舒, 亞亠仂仄亠亳亠从亳亠 仗亠仂弍舒亰仂于舒仆亳 (仗仂于仂仂, 于舒亠仆亳亠)
- 62. IBM 2250, Adage亠于舒 仂亟亠仍仆舒 亞舒亳亠从舒 舒仆亳, 弍亶 亟亳仗仍亠亶 (于舒亠仆亳亠 弍亠亰 仄亠舒仆亳)1024x1024 于亠从仂仆亶 亟亳仗仍亠亶, 从仂于舒仍 从 IBM 360
- 63. Virtual Reality, Harvard, 1968Ivan Sutherland 仗亠亠亠仍 于 舒于舒亟, 亞亟亠 舒亰舒弍仂舒仍 仗亠于亶 Head Mounted Display (HMD)亳舒仍仆舒 从仂仄仆舒舒 (wireframe), 于 从仂仂 仄仂亢仆仂 于仂亶亳
- 64. Utah, 1968 亳 亟舒仍亠亠Hidden surface (Romney, Warnock, Watkins)scan line coherence (Watkins)Rendering (Crow, Blinn, Newell, Catmull, Clark, etal)z-buffer (Catmull)Patch rendering (Catmull)Texture mapping (Catmull, Blinn, Newell)Shadows (Crow)Antialiasing (Crow)Shading (Phong, Gouraud)Lighting (Phong, Blinn)Atmospheric effects (Blinn)Environment mapping (Blinn, Newell)Blobby surfaces (Blinn)Facial animation (Parke)Procedural modeling (Newell)Splines (Riesenfeld, Lyche, Cohen)Beta-splines (Barsky)
- 65. Freddy II, 1973丕仆亳于亠亳亠 亅亟亳仆弍亞舒亟亳仆 亳亰 仗亠于 仂弍仂仂于 亳亠仄仂亶 仄舒亳仆仆仂亞仂 亰亠仆亳5 亠仗亠仆亠亶 于仂弍仂亟丕仄亠亠 仂弍亳舒 仄舒亳仆从亳 亳亰 从弍亳从仂于, 舒亰弍仂舒仆仆 仗仂 仂仍384弍 RAM 于 仗舒于仍ﾑ亠仄 从仂仄仗ﾑ亠亠
- 66. 舒于亳亟 舒 (1970亠)束Primal sketch損亳亰从仂仂于仆亠于亠 (束low-level損) 于仂亶于舒 亳亰仂弍舒亢亠仆亳: 仆舒仗舒于仍亠仆仆亠 从舒, 仂亠亰从亳 亳 .亟.束2.5D sketch損丕仗仂磲仂亳于舒仆亳亠 仗仂 亞仍弍亳仆亠 (弍亳仆仂从仍仆仂亠 亠仂亠), 亠从 亳 .亟.束3D model損舒仗仂亰仆舒于舒仆亳亠 仂弍亠从仂于 亳 仗亠亟舒于仍亠仆亳亠 仂 3 仄亠仆仂仄 仄亳亠
- 67. 亠舒亠仄亠 亰舒亟舒亳亰仂弍舒亢亠仆亳 亳 于亳亟亠仂 仗仂于ﾐ観仆仂 舒舒 仂弍仍舒弍舒弍仂从舒 仍亠仆亳亠 从舒亠于舒, 亠, 亳亰仄亠仆亠仆亳亠 舒亰仄亠舒 亳 仂仄, 从仂仄仗仂亰亳亳仆亠仆亠 仗仂亳从, 舒仆仆仂舒亳, 仗仂亳从 亟弍仍亳从舒仂于, 舒仗仂亰仆舒于舒仆亳亠 仂弍亠从仂于亳亟亠仂仆舒弍仍ﾐ莞黍出湖 仂仍亠亢亳于舒仆亳亠, 舒仗仂亰仆舒于舒仆亳亠 仂弍亠从仂于, 舒仗仂亰仆舒于舒仆亳亠 亢亠仂于 亳 仂弍亳亶仂仄仍亠仆仆亠 亳亠仄 亟亳舒亞仆仂亳从舒, 从仂仆仂仍 从舒亠于舒弌仗亠亠从 于 从亳仆仂 从仂仄仗仂亰亳亳, 仄仂仆舒亢 仂仆仂于, 亰舒于舒 亟于亳亢亠仆亳
- 68. Personal photo albumsMovies, news, sportsMedical and scientific imagesSurveillance and security舒仗仂舒仆亠仆亳亠 亳亰仂弍舒亢亠仆亳亶
- 69. 舒仗仂亰仆舒于舒仆亳亠 亠从舒Digit recognition, AT&T labshttp://www.research.att.com/~yann/License plate readershttp://en.wikipedia.org/wiki/Automatic_number_plate_recognitionSource: S. Seitz
- 70. 亠亠从仂 仍亳 (2001)仍亞仂亳仄 Viola-Jones 仗亠于亶 弍亶 亳 仆舒亟亠亢仆亶 舒仍亞仂亳仄 仗仂亳从舒 仍亳. 亠仄仂仆舒亳 亳仍 仄舒亳仆仆仂亞仂 仂弍亠仆亳.Source: S. Seitz
- 71. 仂亳从 仍弍从亳Sony Cyber-shot速 T70 Digital Still Camera Source: S. Seitz
- 72. 舒仗仂亰仆舒于舒仆亳亠 仍亳仂 仂仆舒?Source: S. Seitz
- 73. 亳仂仄亠亳How the Afghan Girl was Identified by Her Iris Patterns Read the story Source: S. Seitz
- 74. 亳仂仄亠亳Face recognition systems now beginning to appear more widelyhttp://www.sensiblevision.com/Fingerprint scanners on many new laptops, other devicesSource: S. Seitz
- 76. 舒仗仂亰仆舒于舒仆亳亠 仂弍亠从仂于Microsoft ResearchSource: S. Seitz
- 77. 丕仄仆亠 仄舒亳仆Mobileye丐仂仗-仄仂亟亠仍亳 仂 BMW, GM, Volvo 2010: 70% 仗仂亳亰于仂亟亳亠仍亠亶 仄舒亳仆Source: S. Seitz
- 78. 丕仄仆亠 仄舒亳仆
- 79. 3D 仄仂亟亠仍亳 亟仍 从亳仆仂The Matrix movies, ESC Entertainment, XYZRGB, NRCSource: S. Seitz
- 80. 舒于舒 亟于亳亢亠仆亳Pirates of the Carribean, Industrial Light and MagicSource: S. Seitz
- 81. 弌仗仂亳于仆亠 仂亠于仆仂于舒仆亳Sportvision first down lineNice explanation on www.howstuffworks.comSource: S. Seitz
- 82. 亠仆亳亠 于 从仂仄仂亠NASA'S Mars Exploration Rover Spirit. 弌亳亠仄 亰亠仆亳 亳仗仂仍亰仂于舒仍亳 亟仍:弌从仍亠亶从舒 仗舒仆仂舒仄
- 84. 仂亳从 仗亠仗于亳亶, 仂仗亠亟亠仍亠仆亳亠 仄亠仂仗仂仍仂亢亠仆亳
- 85. 仂亟仂弍仆亠亠 仄. Computer Vision on Mars by Matthies et al.Source: S. Seitz
- 87. 亠仆亳亠 仂弍仂仂于NASAs Mars Spirit Roverhttp://en.wikipedia.org/wiki/Spirit_roverhttp://www.robocup.org/Source: S. Seitz
- 88. 丐亠仄亠仆亠 从舒Image from Microsofts Virtual Earth(see also: Google Earth)Source: S. Seitz
- 89. PhotoSynth
- 90. PhotoSynth
- 91. 亳仄亠 仆舒亳 亰舒亟舒3D 亠从仂仆从亳 亰亟舒仆亳亶仂仂亢仆亠 仍舒弍仂舒仂亳亳亳亟亠仂仆舒弍仍ﾐ莞黍出湖黍舒亰仆亠 亰舒亟舒亳
- 92. 亠从仂仆从亳 亞仂仂亟仂于
- 93. 仂仂亢仆亠 仍舒弍仂舒仂亳亳
- 94. 亳亟亠仂仆舒弍仍ﾐ莞黍出湖
- 95. 舒亰仆仂亠 (MSR)仂亳从 亠从舒 于 亳亰仂弍舒亢亠仆亳磪从舒 亠亞仄亠仆舒亳 于亳亟亠仂
- 96. 弌从舒 从舒13 仍亠从亳亶4 亟仂仄舒仆亳 亰舒亟舒仆亳亠仆从亳 亰舒 亰舒亟舒仆亳 (2...5)亠仆从舒 亰舒 从 仗仂 亰舒亟舒仆亳礆.弍. 仗亳仄亠仆仆亠 仗舒亢仆亠仆亳舒亟舒仆亳 仆舒 舒仍舒弍丕亟仂弍仆亠亠 亳 仗仂亠, 亠仄 仆舒 弌++/弌#亟亠 亰舒仆亳亠 仗仂 舒仍舒弍!仂仗仂: 仂仄 http://forum.graphicon.ru
- 97. 仂仄舒仆亳亠 亰舒亟舒仆亳碻亳亠仄舒 舒仗仂亰仆舒于舒仆亳 舒于仂仄仂弍亳仍仆 仆仂仄亠仂于 于 3 舒
- 98. 舒仗仂亰仆舒于舒仆亳亠 亳
- 99. 仂亳从 仆仂仄亠仂于 于 亳亰仂弍舒亢亠仆亳亳
- 101. 舒仆仆亠 仗亠亟仂舒于仍亠仆 从仂仄仗舒仆亳亠亶 ISS: www.iss.ru仂亞舒仄仄舒 从舒于亠亟亠仆亳亠 于 从仂仄仗ﾑ亠仆仂亠 亰亠仆亳亠 (于亠仆舒)Low-level vision弍舒弍仂从舒 亳亰仂弍舒亢亠仆亳亶 亳 仍仂从舒仍仆亠 仂仂弍亠仆仆仂亳Mid-level vision弌仂仗仂舒于仍亠仆亳亠 亳亰仂弍舒亢亠仆亳亶 亳 仄亠仂亟 亞仗仗亳仂于从亳, 亠亞仄亠仆舒亳High-level vision舒仗仂亰仆舒于舒仆亳亠 亳亰仂弍舒亢亠仆亳亶, 仗仂亳从 亳亰仂弍舒亢亠仆亳亶舒亰仆亠 亰舒亟舒亳仂仗. 仍舒于 从仂仄仗ﾑ亠仆仂亞仂 亰亠仆亳 (仂亠仆)仆舒仍亳亰 于亳亟亠仂 亳 于亳亟亠仂仆舒弍仍ﾐ莞黍出湖黍仆舒仍亳亰 亳亰仂弍舒亢亠仆亳亶 亠仍仂于亠从舒 (仍亳仂, 仗仂亰舒)丐仄亠仆舒 亠从仂仆从亳 仗仂 亳亰仂弍舒亢亠仆亳礆
- 102. =*Linear filteringEdge detection弍舒弍仂从舒 亳亰仂弍舒亢亠仆亳亶
- 103. 亠亟舒于仍亠仆亳亠 亳亰仂弍舒亢亠仆亳亶丼舒仂仆舒 亳仍舒亳 亳亰仂弍舒亢亠仆亳, JPEG亳舒仄亳亟 亳亰仂弍舒亢亠仆亳亶弌仍仂于舒亳, 舒亰亠亢亠仆仆仂亠 仗亠亟舒于仍亠仆亳亠
- 104. (x,y)r(x0,y0)s縁縁駕頴仂从舒仍仆亠 仂仂弍亠仆仆仂亳亰于仍亠亠仆亳亠, 仂仗亳舒仆亳亠, 仂仗仂舒于仍亠仆亳亠
- 105. AlignmentFitting: Least squaresHough transformRANSAC弌仂仗仂舒于仍亠仆亳亠 亳亰仂弍舒亢亠仆亳亶
- 106. 舒亠亞仂亳亰舒亳 亳亰仂弍舒亢亠仆亳亶+ 亠仂亟 从仍舒亳亳从舒亳亳 亳 仄舒亳仆仆仂亞仂 仂弍亠仆亳
- 107. 舒亳仆仆仂亠 仂弍亠仆亳亠亠仂亟 仂仗仂仆 于亠从仂仂于亳仆亞亠仆从舒 从仍舒亳亳从舒仂仂于
- 108. 仂亳从 亳 仍仂从舒仍亳亰舒亳 仂弍亠从仂于
- 109. 亠仂亟 仆舒 从仂仍仍亠从亳 从舒亳仆仂从
- 110. 仂亳从 亳亰仂弍舒亢亠仆亳亶于 弍舒亰亠
- 112. 弌亠仄舒仆亳亠从舒 亠亞仄亠仆舒亳
- 113. 丶亳仂于仂亶 仂仂仄仂仆舒亢
- 114. 丼舒 2: 仆舒仍亳亰 于亳亟亠仂
- 115. 丼舒 2: 亰仂弍舒亢亠仆亳 亠仍仂于亠从舒Motion and trackingArticulated models
- 116. 丼舒 2: 丐亠仄亠仆舒 亠从仂仆从亳
Editor's Notes
- #44: 仗舒 仗亠亠亟 舒仆亰从仂亶 舒从舒亟亠仄亳亠亶 仆舒从
- #45: 于仂 舒亳仆于亠仆仆仂 仗仂仗舒仍 仗仂亠亰亟舒. 舒舒 亰舒亠仍亳仍亳 仗仂仍亠 仗舒亠仆仆仂亞仂 亟舒 亅亟亳仂仆仂仄
- #47: 1909 - 舒仂仂仂亠仄从舒
- #60: Low-level image processing algorithms are applied to 2D images to obtain the ``primal sketch(directed edge segments, etc.), from which a 2.5 D sketch of the scene is obtained using binocularstereo. Finally, high-level (structural analysis, a priori knowledge) techniques are used to get 3Dmodel representations of the objects in the scene. This is probably the single most influential workin computer vision ever. Many researchers cried: ``From the paradigm created for us by Marr, noone can drive us out.
- #80: 弌ﾐ莞 仄仂亢仆仂 于舒于亳 于亳亟亠仂