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

Lec 1 : Introduction to Computer Vision

Lec 2 : Introduction to Digital Image Processing

Lec 3 : Image Formation: Radiometry

Lec 4 : Shape From Shading

Lec 5 : Image Formation: Geometric Camera Models - I

Lec 6 : Image Formation: Geometric Camera Model - II

Lec 7 : Image Formation: Geometric Camera Model - III

Lec 8 : Image Formation in a Stereo Vision Setup

Lec 9 : Image Reconstruction from a Series of Projections

Lec 10 : Image Reconstruction from a Series of Projections

Lec 11 : Image Transforms - I

Lec 12 : Image Transforms - II

Lec 13 : Image Transforms - III

Lec 14 : Image Transforms - IV

Lec 15 : Image Enhancement.

Lec 16 : Image Filtering-I

Lec 17 : Image Filtering-II

Lec 18 : Colour Image Processing - I

Lec 19 : Colour Image Processing - II

Lec 20 : Image Segmentation

Lec 21 : Image Features and Edge Detection

Lec 22 : Edge Detection

Lec 23 : Hough Transform

Lec 24 : Image Texture Analysis - I

Lec 25 : Image Texture Analysis - II

Lec 26 : Object Boundary and Shape Representations - I

Lec 27 : Object Boundary and Shape Representations - II

Lec 28 : Interest Point Detectors

Lec 29 : Image Features - HOG and SIFT

Lec 30 : Introduction to Machine Learning - I

Lec 31 : Introduction to Machine Learning - II

Lec 32 : Introduction to Machine Learning - III

Lec 33 : Introduction to Machine Learning - IV

Lec 34 : Introduction to Machine Learning - V

Lec 35 : Artificial Neural Network for Pattern Classification - I

Lec 36 : Artificial Neural Network for Pattern Classification - II

Lec 37 : Introduction to Deep Learning

Lec 38 : Gesture Recognition

Lec 39 : Background Modelling and Motion Estimation

Lec 40 : Object Tracking

Lec 41 : Programming Examples

Description:

PRE-REQUISITES: Basic co-ordinate geometry, matrix algebra, linear algebra and random process. INTENDED AUDIENCE: UG, PG and Ph.D. students INDUSTRIES APPLICABLE TO: The software industries that develop computer visions apps would be benefitted from this course. COURSE OUTLINE: The intent of this course is to familiarize the students to explain the fundamental concepts/issues of Computer Vision and Image Processing, and major approaches that address them. Even though Computer Vision is being used for many practical applications today, it is still not a "solved" problem. Hence, definitive solutions are available only rarely.

Computer Vision and Image Processing - Fundamentals and Applications

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#Computer Science #Artificial Intelligence #Computer Vision #Digital Image Processing #Image Processing #Image Segmentation #Image Filtering #Image Enhancement #Edge Detection #Image Reconstruction

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