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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

The orthogonal Procrustes problem

Originally, this problem questioned ways of finding orthogonal transformation between two matrices. Maybe that doesn't sound relevant to real computer vision applications, but that feeling may change when you consider the fact that a set of points is indeed a matrix. Camera calibration, rigid body transformations, photogrammetry issues, and many other tasks require solving of the orthogonal Procrustes problem. In this recipe, we find a solution to the simple task of estimation point set rotation and examine how our solution is influenced by noisy input data.

Getting ready

Before you proceed with this recipe, you need to install the OpenCV 3.0 (or greater) Python API package.

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