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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

You're reading from   Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA Effective techniques for processing complex image data in real time using GPUs

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789348293
Length 380 pages
Edition 1st Edition
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Author (1):
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Bhaumik Vaidya Bhaumik Vaidya
Author Profile Icon Bhaumik Vaidya
Bhaumik Vaidya
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Table of Contents (15) Chapters Close

Preface 1. Introducing CUDA and Getting Started with CUDA 2. Parallel Programming using CUDA C FREE CHAPTER 3. Threads, Synchronization, and Memory 4. Advanced Concepts in CUDA 5. Getting Started with OpenCV with CUDA Support 6. Basic Computer Vision Operations Using OpenCV and CUDA 7. Object Detection and Tracking Using OpenCV and CUDA 8. Introduction to the Jetson TX1 Development Board and Installing OpenCV on Jetson TX1 9. Deploying Computer Vision Applications on Jetson TX1 10. Getting Started with PyCUDA 11. Working with PyCUDA 12. Basic Computer Vision Applications Using PyCUDA 13. Assessments 14. Other Books You May Enjoy

Introduction to OpenCV

OpenCV is a computer vision library developed with computational efficiency in mind and keeping the focus on real-time performance. It is written in C/C++ and it contains more than a hundred functions that help in computer vision applications. The main advantage of OpenCV is that it is open source and released under a Berkley software distribution (BSD) license which allows free use of OpenCV in research and commercial applications. This library has an interface in C, C++, Java, and Python languages and it can be used in all operating systems, such as Windows, Linux, macOS, and Android, without modifying a single line of code.

This library can also take advantage of multi-core processing and OpenGL and CUDA for parallel processing. As OpenCV is lightweight, it can be used on embedded platforms such as Raspberry Pi as well. This makes it ideal for deploying...

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