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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

Getting started II: Accessing the camera live feed using OpenCV


Next we need to demonstrate how to integrate OpenCV into our Android-based development framework. The following block diagram illustrates the core functions and relationship among the classes that will be implemented in this chapter (only the functions or classes relevant to the introduction of OpenCV will be discussed in this section):

In particular, we will demonstrate how to extract an image frame from the camera video stream for further image processing steps. The OpenCV library provides camera support for accessing the live camera feed (the raw data buffer of the video data stream) as well as controlling the camera parameters. This feature allows us to get the raw frame data from the live preview camera with optimal resolution, frame rate, and image format.

Getting ready

The demos in this chapter build upon the basic structure introduced in the sample code of Chapter 8, Interactive Real-time Data Visualization on Mobile Devices...

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