Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Augmented reality with jMonkeyEngine


Having calibrated the camera, we can proceed with implementing our AR application. We will make a very simple application that only shows a plain 3D box on top of the marker, using the jMonkeyEngine (JME) 3D rendering suite. JME is very feature-rich, and full-blown games are implemented using it (such as Rising World); we could extend our AR application into a real AR game with additional work. When looking over this chapter, the code needed to create a JME application is much more extensive than what we will see here, and the full code is available in the book's code repository.

To start, we need to provision JME to show the view from the camera behind the overlaid 3D graphics. We will create a texture to store the RGB image pixels, and a quad to show the texture. The quad will be rendered by an orthographic camera (without perspective), since it's a simple 2D image without depth.

The following code will create a Quad, a simple, flat, four-vertex 3D object...