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OpenCV 4 Computer Vision Application Programming Cookbook

OpenCV 4 Computer Vision Application Programming Cookbook

By : Millán Escrivá, Robert Laganiere
5 (1)
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OpenCV 4 Computer Vision Application Programming Cookbook

OpenCV 4 Computer Vision Application Programming Cookbook

5 (1)
By: Millán Escrivá, Robert Laganiere

Overview of this book

OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work with recipes to implement a variety of tasks. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by guiding you through setting up OpenCV, and explaining how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of this book, you'll have the skills you need to confidently implement a range of computer vision algorithms to meet the technical requirements of your complex CV projects.
Table of Contents (17 chapters)
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Tracking an object in a video

In the previous two recipes, we learned how to track the motion of points and pixels in an image sequence. In many applications, however, the usual requirement is to track a specific moving object in a video. An object of interest is first identified, and then it must be followed over a long sequence. This is challenging because, as it evolves in the scene, the image of this object will undergo many changes in appearance due to viewpoint and illumination variations, non-rigid motion, occlusion, and more.

This recipe presents some of the object-tracking algorithms implemented in the OpenCV library. These implementations are based on a common framework, which facilitates the substitution of one method by another. Contributors have also made a number of new methods available. Note that we have already presented a solution to the object-tracking problem...

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