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OpenCV 4 with Python Blueprints

You're reading from   OpenCV 4 with Python Blueprints Build creative computer vision projects with the latest version of OpenCV 4 and Python 3

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789801811
Length 366 pages
Edition 2nd Edition
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Authors (4):
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Michael Beyeler (USD) Michael Beyeler (USD)
Author Profile Icon Michael Beyeler (USD)
Michael Beyeler (USD)
Dr. Menua Gevorgyan Dr. Menua Gevorgyan
Author Profile Icon Dr. Menua Gevorgyan
Dr. Menua Gevorgyan
Michael Beyeler Michael Beyeler
Author Profile Icon Michael Beyeler
Michael Beyeler
Arsen Mamikonyan Arsen Mamikonyan
Author Profile Icon Arsen Mamikonyan
Arsen Mamikonyan
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Table of Contents (14) Chapters Close

Preface 1. Fun with Filters 2. Hand Gesture Recognition Using a Kinect Depth Sensor FREE CHAPTER 3. Finding Objects via Feature Matching and Perspective Transforms 4. 3D Scene Reconstruction Using Structure from Motion 5. Using Computational Photography with OpenCV 6. Tracking Visually Salient Objects 7. Learning to Recognize Traffic Signs 8. Learning to Recognize Facial Emotions 9. Learning to Classify and Localize Objects 10. Learning to Detect and Track Objects 11. Profiling and Accelerating Your Apps 12. Setting Up a Docker Container 13. Other Books You May Enjoy

Preface

The goal of this book is to get you hands-on with a wide range of intermediate to advanced projects using the latest version of the OpenCV 4 framework and the Python 3.8 language instead of only covering the core concepts of computer vision in theoretical lessons.

This updated second edition has increased the depth of the concepts we tackle with OpenCV. It will guide you through working on independent hands-on projects that focus on essential computer vision concepts such as image processing, 3D scene reconstruction, object detection, and object tracking. It will also cover, with real-life examples, statistical learning and deep neural networks.

You will begin by understanding concepts such as image filters and feature matching, as well as using custom sensors such as the Kinect depth sensor. You will also learn how to reconstruct and visualize a scene in 3D, how to align images, and how to combine multiple images into a single one. As you advance through the book, you will learn how to recognize traffic signs and emotions on faces and detect and track objects in video streams using neural networks, even if they disappear for short periods of time.

By the end of this OpenCV and Python book, you will have hands-on experience and be proficient at developing your own advanced computer vision applications according to specific business needs. Throughout the book, you will explore multiple machine learning and computer vision models such as Support Vector Machines (SVMs) and convolutional neural networks.

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