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OpenCV 4 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications with OpenCV and C++

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789340723
Length 494 pages
Edition 4th Edition
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Authors (2):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
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Table of Contents (17) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating the Pixels 3. Processing Color Images with Classes 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples 15. OpenCV Advanced Features 16. Other Books You May Enjoy

Extracting the foreground objects in a video

When a fixed camera observes a scene, the background remains mostly unchanged. In this case, the interesting elements are the moving objects that evolve inside this scene. In order to extract these foreground objects, we need to build a model of the background, and then compare this model with a current frame in order to detect any foreground objects. This is what we will do in this recipe. Foreground extraction is a fundamental step in intelligent surveillance applications.

If we had an image of the background of the scene (that is, a frame that contains no foreground objects) at our disposal, then it would be easy to extract the foreground of a current frame through a simple image difference:

  // compute difference between current image and background 
  cv::absdiff(backgroundImage,currentImage,foreground); 

Each pixel for which...

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