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Learning OpenCV 5 Computer Vision with Python

You're reading from   Learning OpenCV 5 Computer Vision with Python Tackle computer vision and machine learning with the newest tools, techniques and algorithms

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Product type Paperback
Published in Jul 2025
Publisher Packt
ISBN-13 9781803230221
Length
Edition 4th Edition
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Authors (2):
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Joe Minichino Joe Minichino
Author Profile Icon Joe Minichino
Joe Minichino
Joseph Howse Joseph Howse
Author Profile Icon Joseph Howse
Joseph Howse
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Table of Contents (12) Chapters Close

1. Learning OpenCV 5 Computer Vision with Python, Fourth Edition: Tackle tools, techniques, and algorithms for computer vision and machine learning FREE CHAPTER
2. Setting Up OpenCV 3. Handling Files, Cameras, and GUIs 4. Processing Images with OpenCV 5. Detecting and Recognizing Faces 6. Retrieving Images and Searching Using Image Descriptors 7. Building Custom Object Detectors 8. Tracking Objects 9. Camera Models and Augmented Reality 10. Introduction to Neural Networks with OpenCV 11. OpenCV Applications at Scale Appendix A: Bending Color Space with the Curves Filter

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If you like geometry, photography, or 3D graphics, then this chapter's topics should especially appeal to you. We will learn about the relationship between 3D space and a 2D projection. We will model this relationship in terms of the basic optical parameters of a camera and lens. Finally, we will apply the same relationship to the task of drawing 3D shapes in an accurate perspective projection. Throughout all of this, we will integrate our previous knowledge of image matching and object tracking in order to track 3D motion of a real-world object whose 2D projection is captured by a camera in real time.

On a practical level, we will build an augmented reality application that uses information about a camera, an object, and motion in order to superimpose 3D graphics on top of a tracked object in real time. To achieve this, we will conquer the following technical challenges:

  • Modeling the parameters of a camera and...
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