This chapter introduced two key topics in computer vision: camera calibration and camera/object pose estimation. We saw the theoretical background for achieving these concepts in practice, as well as their implementation in OpenCV using the aruco contrib module. Finally, we built an Android application that runs the ArUco code in native functions to calibrate the camera and then detect the AR marker. We used the jMonkeyEngine 3D rendering engine to create a very simple augmented reality application using ArUco calibration and detection.
In the next chapter, we will see how to use OpenCV in an iOS app environment to build a panorama stitching application. Using OpenCV in a mobile environment is a very popular feature of OpenCV, as the library provides pre-built binaries and releases for both Android and iOS.