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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 Jetson TX1

When high-end visual computing and computer vision applications need to be deployed in real-life scenarios, then embedded development platforms are required, which can do computationally intensive tasks efficiently. Platforms such as Raspberry Pi can use OpenCV for computer vision applications and camera-interfacing capability, but it is very slow for real-time applications. Nvidia, which specializes in GPU manufacturing, has developed modules that use GPUs for computationally intensive tasks. These modules can be used to deploy computer vision applications on embedded platforms and include Jetson TK1, Jetson TX1, and Jetson TX2.

Jetson TK1 is the preliminary board and contains 192 CUDA cores with the Nvidia Kepler GPU. It is the cheapest of the three. Jetson TX1 is intermediate in terms of processing speed, with 256 CUDA cores with Maxwell architecture...

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