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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

Getting Started with OpenCV with CUDA Support

So far, we have seen all the concepts related to parallel programming using CUDA and how it can leverage the GPU for acceleration. From this chapter on, we will try to use the concept of parallel programming in CUDA for computer vision applications. Though we have worked on matrices, we have not worked on actual images. Basically, working on images is similar to manipulation of two-dimensional matrices. We will not develop the entire code from scratch for computer vision applications in CUDA, but we will use the popular computer vision library that is called OpenCV. Though this book assumes that the reader has some familiarity with working with OpenCV, this chapter revises the concepts of using OpenCV in C++. This chapter describes the installation of the OpenCV library with CUDA support on Windows and Ubuntu. Then it describes how...

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