Detect and decode patterns known as ArUco markers, which are small 2D barcodes often used in augmented reality and robotics.
ArUco markers are small 2D barcodes. Each ArUco marker corresponds to a number, encoded into a small grid of black and white pixels. The ArUco decoding algorithm is capable of locating, decoding, and of estimating the pose (location and orientation in space) of any ArUco markers in the camera's field of view.
ArUco markers are very useful as tags for many robotics and augmented reality applications. For example, one may place an ArUco next to a robot's charging station, an elevator button, or an object that a robot should manipulate.
For more information about ArUco, see https://www.uco.es/investiga/grupos/ava/node/26
The implementation of ArUco used by JeVois is the one of OpenCV-Contrib, documented here: http://docs.opencv.org/3.2.0/d5/dae/tutorial_aruco_detection.html
ArUco markers can be created with several standard dictionaries. Different dictionaries give rise to different numbers of pixels in the markers, and to different numbers of possible symbols that can be created using the dictionary. The default dictionary used by JeVois is 4x4 with 50 symbols. Other dictionaries are also supported by setting the parameter
We have created the 50 markers available in the default dictionary (4x4_50) as PNG images that you can download and print, at http://jevois.org/data/ArUco.zip
To make your own, for example, using another dictionary, see the documentation of the ArUco component of JeVoisBase. Some utilities are provided with the component.
This module can send standardized serial messages as described in Standardized serial messages formatting.
One message is issued for every detected ArUco, on every video frame.
2D messages when
3D messages when
If you will use the quaternion data (Detail message style; see Standardized serial messages formatting), you should probably set the
See Standardized serial messages formatting for more on standardized serial messages, and Helper functions to convert coordinates from camera resolution to standardized for more info on standardized coordinates.
The OpenCV ArUco module can also compute the 3D location and orientation of each marker in the world when
When doing pose estimation, you should set the
Check out this tutorial on how to build a simple visually-guided toy robot car for under $100 with JeVois, which uses ArUco at its core. A demo video is here: