Book Image

OpenGL Data Visualization Cookbook

Book Image

OpenGL Data Visualization Cookbook

Overview of this book

OpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications. This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapter addresses different visualization problems encountered in real life and introduces the relevant OpenGL features and libraries in a modular fashion. By the end of this book, you will be equipped with the essential skills to develop a wide range of impressive OpenGL-based applications for your unique data visualization needs, on platforms ranging from conventional computers to the latest mobile/wearable devices.
Table of Contents (16 chapters)
OpenGL Data Visualization Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Augmented reality-based data visualization over real-world scenes


In our ultimate demo, we will introduce the basic framework for AR-based data visualization by overlaying 3D data on real-world objects and scenes. We apply the same GPU-accelerated simulation model and register it to the world with a sensor-based tracking approach. The following diagram illustrates the final architecture of the implementation in this chapter:

Getting ready

This final demo integrates together all the concepts previously introduced in this chapter and requires the capture (and possibly processing) of a real-time video stream using OpenCV on an Android-based phone. To reduce the complexity of the code, we have created the Augmented Reality layer (AROverlayRenderer) and we can improve the registration, alignment, and calibration of the layer with more advanced algorithms in the future.

How to do it...

Let's define a new class called AROverlayRenderer inside the AROverlayRenderer.hpp file:

#ifndef AROVERLAYRENDERER_H_...