Basics of Reading Fiduciary Markers
Explore the step-by-step process of reading fiduciary markers using Python and OpenCV. Learn how to perform camera calibration, capture and preprocess images, detect markers, estimate pose, post-process data, and visualize results for applications including augmented reality.
Reading and detecting fiduciary markers like ArUco markers and AprilTags involves several steps. Here is an overview of the process:
- Camera calibration (optional but recommended)
- Capture images or video frames
- Preprocessing
- Marker detection
- Pose estimation (optional)
- Post-processing (optional)
- Visualization (required for AR, otherwise optional)
The marker detection process
Here, we’ll give a short discussion of ...