Computer Vision and Image Processing - Fundamentals and Applications

Computer Vision and Image Processing - Fundamentals and Applications

NPTEL IIT Guwahati via YouTube Direct link

Computer Vision and Image Processing – Fundamentals and Applications [Intro Video]

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1 of 42

Computer Vision and Image Processing – Fundamentals and Applications [Intro Video]

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Computer Vision and Image Processing - Fundamentals and Applications

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  1. 1 Computer Vision and Image Processing – Fundamentals and Applications [Intro Video]
  2. 2 Lec 1 : Introduction to Computer Vision
  3. 3 Lec 2 : Introduction to Digital Image Processing
  4. 4 Lec 3 : Image Formation: Radiometry
  5. 5 Lec 4 : Shape From Shading
  6. 6 Lec 5 : Image Formation: Geometric Camera Models - I
  7. 7 Lec 6 : Image Formation: Geometric Camera Model - II
  8. 8 Lec 7 : Image Formation: Geometric Camera Model - III
  9. 9 Lec 8 : Image Formation in a Stereo Vision Setup
  10. 10 Lec 9 : Image Reconstruction from a Series of Projections
  11. 11 Lec 10 : Image Reconstruction from a Series of Projections
  12. 12 Lec 11 : Image Transforms - I
  13. 13 Lec 12 : Image Transforms - II
  14. 14 Lec 13 : Image Transforms - III
  15. 15 Lec 14 : Image Transforms - IV
  16. 16 Lec 15 : Image Enhancement.
  17. 17 Lec 16 : Image Filtering-I
  18. 18 Lec 17 : Image Filtering-II
  19. 19 Lec 18 : Colour Image Processing - I
  20. 20 Lec 19 : Colour Image Processing - II
  21. 21 Lec 20 : Image Segmentation
  22. 22 Lec 21 : Image Features and Edge Detection
  23. 23 Lec 22 : Edge Detection
  24. 24 Lec 23 : Hough Transform
  25. 25 Lec 24 : Image Texture Analysis - I
  26. 26 Lec 25 : Image Texture Analysis - II
  27. 27 Lec 26 : Object Boundary and Shape Representations - I
  28. 28 Lec 27 : Object Boundary and Shape Representations - II
  29. 29 Lec 28 : Interest Point Detectors
  30. 30 Lec 29 : Image Features - HOG and SIFT
  31. 31 Lec 30 : Introduction to Machine Learning - I
  32. 32 Lec 31 : Introduction to Machine Learning - II
  33. 33 Lec 32 : Introduction to Machine Learning - III
  34. 34 Lec 33 : Introduction to Machine Learning - IV
  35. 35 Lec 34 : Introduction to Machine Learning - V
  36. 36 Lec 35 : Artificial Neural Network for Pattern Classification - I
  37. 37 Lec 36 : Artificial Neural Network for Pattern Classification - II
  38. 38 Lec 37 : Introduction to Deep Learning
  39. 39 Lec 38 : Gesture Recognition
  40. 40 Lec 39 : Background Modelling and Motion Estimation
  41. 41 Lec 40 : Object Tracking
  42. 42 Lec 41 : Programming Examples

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