Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By : David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
Book Image

Building Computer Vision Projects with OpenCV 4 and C++

By: David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot

Overview of this book

OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: •Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá •Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Table of Contents (28 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Panoramic image stitching methods


Panoramas are essentially multiple images fused together into a single image. The process of panorama creation from multiple images involves many steps; some are common to other computer vision tasks, such as the following:

  • Extracting 2D features
  • Matching pairs of images based on their features
  • Transforming or warping images to a communal frame 
  • Using (blending) the seams between the images for the pleasing continuous effect of a larger image

Some of these basic operations are also commonplace in Structure-from-Motion (SfM), 3D reconstruction , visual odometry, and simultaneous localization and mapping (SLAM). We've already discussed some of these in Chapter 14Explore Structure from Motion with the SfM Module and Chapter 18Android Camera Calibration and AR Using the ArUco Module. The following is a rough image of the panorama creation process:

In this section, we will briefly review feature matching, camera pose estimation, and image warping. In reality, panorama...