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OpenCV 3 Computer Vision with Python Cookbook

You're reading from   OpenCV 3 Computer Vision with Python Cookbook Leverage the power of OpenCV 3 and Python to build computer vision applications

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788474443
Length 306 pages
Edition 1st Edition
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Authors (2):
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Aleksandr Rybnikov Aleksandr Rybnikov
Author Profile Icon Aleksandr Rybnikov
Aleksandr Rybnikov
Aleksei Spizhevoi Aleksei Spizhevoi
Author Profile Icon Aleksei Spizhevoi
Aleksei Spizhevoi
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Toc

Table of Contents (11) Chapters Close

Preface 1. I/O and GUI FREE CHAPTER 2. Matrices, Colors, and Filters 3. Contours and Segmentation 4. Object Detection and Machine Learning 5. Deep Learning 6. Linear Algebra 7. Detectors and Descriptors 8. Image and Video Processing 9. Multiple View Geometry 10. Other Books You May Enjoy

Detecting AruCo patterns for AR applications

Understanding a camera's position in a surrounding 3D space is a very challenging and hard-to-solve task. Specifically designed patterns, named AruCo markers, are called up to solve this issue. Each marker has enough information to determine the camera position, and also contains information about itself; so it's possible to distinguish between different markers, and, through that, understand the scene. In this recipe, we will review how to create and detect AruCo markers with OpenCV.

Getting ready

Before you proceed with this recipe, you will need to install the OpenCV 3.x Python API package with the OpenCV contrib modules.

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