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OpenGL Data Visualization Cookbook

OpenGL Data Visualization Cookbook

4.6 (5)
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OpenGL Data Visualization Cookbook

OpenGL Data Visualization Cookbook

4.6 (5)

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 (11 chapters)
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10
Index

Displaying real-time video using texture mapping


Today, most mobile phones are equipped with cameras that are capable of capturing high-quality photos as well as videos. For example, the Samsung Galaxy Note 4 is equipped with a 16MP back-facing camera as well as a 3.7MP front-facing camera for video conferencing applications. With these built-in cameras, we can record high-definition videos with exceptional image quality in both outdoor and indoor environments. The ubiquity of these imaging sensors, as well as the increasing computational capability of mobile processors, now enable us to develop much more interactive applications such as real-time tracking of objects or faces.

By combining OpenGL with the OpenCV library, we can create interactive applications that perform real-time video processing of the real world to register and augment 3D virtual information onto real-world objects. Since both libraries are hardware-accelerated (GPU and CPU optimized), it is important that we explore...

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