luoyc a9c35a4807 opencv source code commit il y a 1 an
..
doc a9c35a4807 opencv source code commit il y a 1 an
include a9c35a4807 opencv source code commit il y a 1 an
misc a9c35a4807 opencv source code commit il y a 1 an
perf a9c35a4807 opencv source code commit il y a 1 an
samples a9c35a4807 opencv source code commit il y a 1 an
src a9c35a4807 opencv source code commit il y a 1 an
test a9c35a4807 opencv source code commit il y a 1 an
tutorials a9c35a4807 opencv source code commit il y a 1 an
CMakeLists.txt a9c35a4807 opencv source code commit il y a 1 an
README.md a9c35a4807 opencv source code commit il y a 1 an

README.md

ArUco Marker Detection

ArUco

ArUco markers are easy to detect pattern grids that yield up to 1024 different patterns. They were built for augmented reality and later used for camera calibration. Since the grid uniquely orients the square, the detection algorithm can determing the pose of the grid.

ChArUco

ArUco markers were improved by interspersing them inside a checkerboard called ChArUco. Checkerboard corner intersections provide more stable corners because the edge location bias on one square is countered by the opposite edge orientation in the connecting square. By interspersing ArUco markers inside the checkerboard, each checkerboard corner gets a label which enables it to be used in complex calibration or pose scenarios where you cannot see all the corners of the checkerboard.

The smallest ChArUco board is 5 checkers and 4 markers called a "Diamond Marker".