Book Image

Mastering OpenCV with Practical Computer Vision Projects

Book Image

Mastering OpenCV with Practical Computer Vision Projects

Overview of this book

Computer Vision is fast becoming an important technology and is used in Mars robots, national security systems, automated factories, driver-less cars, and medical image analysis to new forms of human-computer interaction. OpenCV is the most common library for computer vision, providing hundreds of complex and fast algorithms. But it has a steep learning curve and limited in-depth tutorials.Mastering OpenCV with Practical Computer Vision Projects is the perfect book for developers with just basic OpenCV skills who want to try practical computer vision projects, as well as the seasoned OpenCV experts who want to add more Computer Vision topics to their skill set or gain more experience with OpenCV's new C++ interface before migrating from the C API to the C++ API.Each chapter is a separate project including the necessary background knowledge, so try them all one-by-one or jump straight to the projects you're most interested in.Create working prototypes from this book including real-time mobile apps, Augmented Reality, 3D shape from video, or track faces & eyes, fluid wall using Kinect, number plate recognition and so on. Mastering OpenCV with Practical Computer Vision Projects gives you rapid training in nine computer vision areas with useful projects.
Table of Contents (15 chapters)
Mastering OpenCV with Practical Computer Vision Projects
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Using the example code


We can find the example code for SfM with the supporting material of this book. We will now see how we can build, run, and make use of it. The code makes use of CMake, a cross-platform build environment similar to Maven or SCons. We should also make sure we have all the following prerequisites to build the application:

  • OpenCV v2.3 or higher

  • PCL v1.6 or higher

  • SSBA v3.0 or higher

First we must set up the build environment. To that end, we may create a folder named build in which all build-related files will go; we will now assume all command-line operations are within the build/folder, although the process is similar (up to the locations of the files) even if not using the build folder.

We should make sure CMake can find SSBA and PCL. If PCL was installed properly, there should not be a problem; however, we must set the correct location to find SSBA's prebuilt binaries via the -DSSBA_LIBRARY_DIR=… build parameter. If we are using Windows as the operating system, we can use...