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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

Object tracking using background subtraction

Background subtraction is the process of separating out foreground objects from the background in a sequence of video frames. It is widely used in object detection and tracking applications to remove the background part. Background subtraction is performed in four steps:

  1. Image preprocessing
  2. Modeling of background
  3. Detection of foreground
  4. Data validation

Image preprocessing is always performed to remove any kind of noise present in the image. The second step is to model the background so that it can be separated from the foreground. In some applications, the first frame of the video is taken as the background and it is not updated. The absolute difference between each frame and the first frame is taken to separate foreground from background.

In other techniques, the background is modeled by taking an average or median of all the frames...

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