Book Image

OpenCV 3.x with Python By Example - Second Edition

By : Gabriel Garrido Calvo, Prateek Joshi
Book Image

OpenCV 3.x with Python By Example - Second Edition

By: Gabriel Garrido Calvo, Prateek Joshi

Overview of this book

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell

Geometric transformations for augmented reality

The result of augmented reality is amazing, but there are a lot of mathematical things going on underneath. Augmented reality utilizes a lot of geometric transformations and associated mathematical functions to make sure everything looks smooth. When talking about a live video for augmented reality, we need to precisely register the virtual objects on top of the real world. To understand this better, let's think of it as an alignment of two cameras: the real one through which we see the world, and the virtual one that projects the computer-generated graphical objects.

In order to build an augmented reality system, the following geometric transformations need to be established:

  • Object-to-scene: This transformation refers to transforming the 3D coordinates of a virtual object and expressing them in the coordinate frame of our real-world scene. This ensures that we are placing the virtual object in the right location.
  • Scene-to-camera: This transformation...