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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 FREE CHAPTER 2. Parallel Programming using CUDA C 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

Basic computer vision applications using the OpenCV CUDA module

In earlier chapters, we saw that CUDA provides an excellent interface to utilize the parallel computing capability of GPU to accelerate complex computing applications. In this section, we will see how we can utilize the capability of CUDA alongside OpenCV for computer vision applications.

Introduction to the OpenCV CUDA module

OpenCV has a CUDA module that has hundreds of functions that can utilize GPU capabilities. It is only supported on Nvidia GPUs because it uses Nvidia CUDA runtime in the background. OpenCV has to be compiled with the WITH_CUDA flag set to ON for using the CUDA module.

One great feature of using the CUDA module of OpenCV is that it provides...

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