NOC:Computer Vision and Image Processing - Fundamentals and Applications
Media Storage Type : 32 GB USB Stick
NPTEL Subject Matter Expert : Prof. M. K. Bhuyan
NPTEL Co-ordinating Institute : IIT Guwahati
NPTEL Lecture Count : 41
NPTEL Course Size : 4.4 GB
NPTEL PDF Text Transcription : Available and Included
NPTEL Subtitle Transcription : Available and Included (SRT)
Lecture Titles:
Lecture 1 - Introduction to Digital Image Processing
Lecture 2 - Introduction to Computer Vision
Lecture 3 - Introduction to Computer Vision and Basic Concepts of Image Formation
Lecture 4 - Shape From Shading
Lecture 5 - Image Formation: Geometric Camera Models - I
Lecture 6 - Image Formation: Geometric Camera Models - II
Lecture 7 - Image Formation: Geometric Camera Models - III
Lecture 8 - Image Formation in a Stereo Vision Setup
Lecture 9 - Image Reconstruction from a Series of Projections
Lecture 10 - Image Reconstruction from a Series of Projections
Lecture 11 - Image Transforms - I
Lecture 12 - Image Transforms - II
Lecture 13 - Image Transforms - III
Lecture 14 - Image Transforms - IV
Lecture 15 - Image Enhancement
Lecture 16 - Image Filtering - I
Lecture 17 - Image Filtering - II
Lecture 18 - Colour Image Processing - I
Lecture 19 - Colour Image Processing - II
Lecture 20 - Image Segmentation
Lecture 21 - Image Features and Edge Detection
Lecture 22 - Edge Detection
Lecture 23 - Hough Transform
Lecture 24 - Image Texture Analysis - I
Lecture 25 - Image Texture Analysis - II
Lecture 26 - Object Boundary and Shape Representations - I
Lecture 27 - Object Boundary and Shape Representations - II
Lecture 28 - Interest Point Detectors
Lecture 29 - Image Features - HOG and SIFT
Lecture 30 - Introduction to Machine Learning - I
Lecture 31 - Introduction to Machine Learning - II
Lecture 32 - Introduction to Machine Learning - III
Lecture 33 - Introduction to Machine Learning - IV
Lecture 34 - Introduction to Machine Learning - V
Lecture 35 - Artificial Neural Network for Pattern Classification - I
Lecture 36 - Artificial Neural Network for Pattern Classification - II
Lecture 37 - Introduction to Deep Learning
Lecture 38 - Gesture Recognition
Lecture 39 - Background Modelling and Motion Estimation
Lecture 40 - Object Tracking
Lecture 41 - Programming Examples