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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

Product type Paperback

Published in Sep 2018

Publisher Packt

ISBN-13 9781789348293

Length 380 pages

Edition 1st Edition

Languages

C++

Tools

CUDA

Concepts

Computer Vision

Author (1):

Bhaumik Vaidya

View More author details

Table of Contents (15) Chapters

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

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Installation of OpenCV with CUDA support

Installation of OpenCV with CUDA is not as trivial as you might think. It involves many steps. In this section, all the steps for installing OpenCV in Windows and Ubuntu are explained with screenshots, so you can set your environment up easily.

Installation of OpenCV on Windows

This section explains the steps needed to install OpenCV with CUDA on a Windows operating system. The steps are performed on the Windows 10 operating system, but it will work on any Windows operating system.

Using pre-built binaries

There are pre-built binaries...

The rest of the chapter is locked

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Authors (1)

Vaidya

Vaidya

Bhaumik Vaidya is an experienced computer vision engineer and mentor. He has worked extensively on OpenCV Library in solving computer vision problems. He is a University gold medalist in masters and is now doing a PhD in the acceleration of computer vision algorithms built using OpenCV and deep learning libraries on GPUs. He has a background in teaching and has guided many projects in computer vision and VLSI(Very-large-scale integration). He has worked in the VLSI domain previously as an ASIC verification engineer, so he has very good knowledge of hardware architectures also. He has published many research papers in reputable journals to his credit. He, along with his PhD mentor, has also received an NVIDIA Jetson TX1 embedded development platform as a research grant from NVIDIA.

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