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Learning OpenCV 4 Computer Vision with Python 3

You're reading from   Learning OpenCV 4 Computer Vision with Python 3 Get to grips with tools, techniques, and algorithms for computer vision and machine learning

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781789531619
Length 372 pages
Edition 3rd Edition
Languages
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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
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Joseph Howse
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Table of Contents (13) Chapters Close

Preface 1. Setting Up OpenCV 2. Handling Files, Cameras, and GUIs FREE CHAPTER 3. Processing Images with OpenCV 4. Depth Estimation and Segmentation 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. Other Book You May Enjoy Appendix A: Bending Color Space with the Curves Filter

Depth Estimation and Segmentation

This chapter begins by showing you how to use data from a depth camera to identify foreground and background regions, such that we can limit an effect to only the foreground or only the background.

After covering depth cameras, the chapter proceeds with other techniques for depth estimation, namely, stereo imaging and structure from motion (SfM). The latter techniques do not require a depth camera; instead, they rely on capturing images of a subject from multiple perspectives with one or more ordinary cameras.

Finally, the chapter covers segmentation techniques that allow us to extract foreground objects from a single image. By the end of the chapter, you will learn several ways to segment an image into multiple depths or multiple objects. Specifically, we will cover the following topics:

  • Using a depth camera to capture depth maps, point cloud...
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