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OpenCV Computer Vision with Java

You're reading from   OpenCV Computer Vision with Java Create multiplatform computer vision desktop and web applications using the combination of OpenCV and Java

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783283972
Length 174 pages
Edition 1st Edition
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Author (1):
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Daniel Lelis Baggio Daniel Lelis Baggio
Author Profile Icon Daniel Lelis Baggio
Daniel Lelis Baggio
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Table of Contents (9) Chapters Close

Preface 1. Setting Up OpenCV for Java FREE CHAPTER 2. Handling Matrices, Files, Cameras, and GUIs 3. Image Filters and Morphological Operators 4. Image Transforms 5. Object Detection Using Ada Boost and Haar Cascades 6. Detecting Foreground and Background Regions and Depth with a Kinect Device 7. OpenCV on the Server Side Index

Background subtraction

When working with surveillance cameras, it's easy to see that most of the frame keeps still, while the moving objects, the ones we are interested in, are the areas that vary most over time. Background subtraction is defined as the approach used to detect moving objects from static cameras, also known as foreground detection, since we're mostly interested in the foreground objects.

In order to perform some valuable background subtraction, it is important to account for varying luminance conditions, taking care always to update our background model. Although some techniques extend the idea of background subtraction beyond its literal meaning, such as the mixture of Gaussian approach, they are still named like this.

In order to compare all the solutions in the following sections, we will come up with a useful interface, which is called VideoProcessor. This interface is made of a simple method called process. The whole interface is given in the following piece...

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