In this section, we are going to see how marker-based augmented reality works. There are many libraries, algorithms, or packages that you can use to both generate and detect markers. In this sense, one that provides state-of-the-art performance in detecting markers is ArUco.
ArUco automatically detects the markers and corrects possible errors. Additionally, ArUco proposes a solution to the occlusion problem by combining multiple markers with an occlusion mask, which is calculated by color segmentation.
As previously commented, pose estimation is a key process in augmented reality applications. Pose estimation can be performed based on markers. The main benefit of using markers is that they can be both efficiently and robustly detected in the image where the four corners of the marker can be accurately derived. Finally, the camera pose can be obtained...
