Beginner’s Guide to Learn Computer Vision with Python

Learn fundamentals of Computer Vision with state of art image and video processing Algorithms.

Course Structure

Introduction:

Introduction
Real world Applications

Popular Computer Vision Techniques:

Image Segmentation
Demo – Image Segmentation
Edge Detection
Demo – Edge Detection
Feature Extraction
Demo – Feature Extraction
Application of CV techniques

Object Detection, Tracking and Classification:

Object Detection
Object Tracking
Image Classification
Demo: Image Classification
Challenges in CV

Deep Learning for Computer Vision:

What is Deep Learning?
Convolutional Neural Network (CNN)
Demo – CNN
Transfer Learning
Benefits of Deep Learning in CV

Image Recognition:

Face Detection and Recognition
Demo – Face Detection
Optical Character Recognition (OCR)
Demo – OCR

Advanced Techniques – Panorama Creation:

Image Registration
Image Stitching
Demo – Image Stitching

Motion Analysis:

Motion Analysis
Video Processing
Background Subtraction
Demo: Background Subtraction

Realtime Video Processing:

Realtime Video Processing
Demo – Object Detection
Application in Robotics

Requirements

Basics knowledge of computer programming
Familiar with python programming language and any python IDE (like PyCharm)
Windows / Linux / Mac OS X Machine with Internet

Content team

Expert: Arunkumar Krishnan
Production: Vishnu Sakthivel, Visshwa Balasubramanian

What you will learn?

Learn fundamentals of Computer Vision
Understand state of art image and video processing Algorithms in CV
Understand application of Deep Learning Models in the CV
Learn to implement CV algorithms with OpenCV python library