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Learning OpenCV 3 Computer Vision with Python (Update)

Learning OpenCV 3 Computer Vision with Python (Update)

By : Joe Minichino, Joseph Howse
2.1 (7)
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Learning OpenCV 3 Computer Vision with Python (Update)

Learning OpenCV 3 Computer Vision with Python (Update)

2.1 (7)
By: Joe Minichino, Joseph Howse

Overview of this book

OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the development of all sorts of real-world applications, including security and surveillance. Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application.
Table of Contents (11 chapters)
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6
6. Retrieving Images and Searching Using Image Descriptors
10
Index

Chapter 5. Detecting and Recognizing Faces

Among the many reasons that make computer vision a fascinating subject is the fact that computer vision makes very futuristic-sounding tasks a reality. One such feature is face detection. OpenCV has a built-in facility to perform face detection, which has virtually infinite applications in the real world in all sorts of contexts, from security to entertainment.

This chapter introduces some of OpenCV's face detection functionalities, along with the data files that define particular types of trackable objects. Specifically, we look at Haar cascade classifiers, which analyze contrast between adjacent image regions to determine whether or not a given image or subimage matches a known type. We consider how to combine multiple Haar cascade classifiers in a hierarchy, such that one classifier identifies a parent region (for our purposes, a face) and other classifiers identify child regions (eyes, nose, and mouth).

We also take a detour into...

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