Detect and track objects in images and videos. Perform accurate and reliable processing tasks with Computer vision using OpenCV
About This Video
- Get a thorough understanding of the OpenCV library and all its functionalities, with practical examples.
- Build a strong foundation for Computer Vision by transforming images and videos using various tools and techniques
- Perform image analysis by controlling, automating, recognizing, and precisely measuring data.
Computer vision solves imaging problems that cannot be solved using ordinary systems and sensors. OpenCV is one of the most popular Computer Vision libraries and helps you write faster code.
This course begins with the basics of loading and working with images. You will detect colored objects in your images easily. You will also use tools to build and apply filters in your photos and track objects in a video.
By the end of the course, you will have a firm grasp of Computer Vision techniques using OpenCV libraries. This course will be your gateway to the world of data science.
The code bundle is placed at: https://github.com/PacktPublishing/Learn-Computer-Vision-with-Python-and-OpenCV-Video
Table of Contents
- Chapter 1 : Get Started with OpenCV Libraries
- Chapter 2 : Detect Colored Objects in Images
- Chapter 3 : Feature Detection Algorithms
Chapter 4 : Video Analysis
- Getting Started with Videos 00:02:38
- Background Subtraction 00:02:16
- Theory Behind Optical Flow 00:02:02
- Optical Flow Using Lucas-Kanade and Dense Optical Flow 00:02:34
- Object Tracking Using Meanshift and Camshift 00:02:43
- Title: Learn Computer Vision with Python and OpenCV
- Release date: October 2018
- Publisher(s): Packt Publishing
- ISBN: 9781788293846