Book Image

Mastering OpenCV 3 - Second Edition

By : Shervin Emami, David Millán Escrivá, Daniel Lelis Baggio, Roy Shilkrot, Eugene Khvedchenia, Jason Saragih
Book Image

Mastering OpenCV 3 - Second Edition

By: Shervin Emami, David Millán Escrivá, Daniel Lelis Baggio, Roy Shilkrot, Eugene Khvedchenia, Jason Saragih

Overview of this book

As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision. This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You’ll learn how to make AI that can remember and use neural networks to help your applications learn. By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3.
Table of Contents (14 chapters)
Title Page
Mastering OpenCV 3 Second Edition
About the Authors
About the Reviewer
Customer Feedback

Accessing the webcam

To access a computer's webcam or camera device, you can simply call the open() function on a cv::VideoCapture object (OpenCV's method of accessing your camera device), and pass 0 as the default camera ID number. Some computers have multiple cameras attached, or they do not work as default camera 0, so it is common practice to allow the user to pass the desired camera number as a command-line argument, in case they want to try camera 1, 2, or -1, for example. We will also try to set the camera resolution to 640x480 using cv::VideoCapture::set() to run faster on high-resolution cameras.


Depending on your camera model, driver, or system, OpenCV might not change the properties of your camera. It is not important for this project, so don't worry if it does not work with your webcam.

You can put this code in the main() function of your main.cpp file:

    int cameraNumber = 0; 
    if (argc> 1) 
    cameraNumber = atoi(argv[1]); 

    // Get access to the camera. 
    cv::VideoCapture camera;; 
    if (!camera.isOpened()) { 
      std::cerr<<"ERROR: Could not access the camera or video!"<< 

    // Try to set the camera resolution. 
    camera.set(cv::CV_CAP_PROP_FRAME_WIDTH, 640); 
    camera.set(cv::CV_CAP_PROP_FRAME_HEIGHT, 480);

After the webcam has been initialized, you can grab the current camera image as a cv::Mat object (OpenCV's image container). You can grab each camera frame by using the C++ streaming operator from your cv::VideoCapture object into a cv::Mat object, just like if you were getting input from a console.


OpenCV makes it very easy to capture frames from a video file (such as an AVI or MP4 file) or network stream instead of a webcam. Instead of passing an integer such as, pass a string such as"my_video.avi") and then grab frames just like it was a webcam. The source code provided with this book has an initCamera() function that opens a webcam, video file, or network stream.