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VOOZH | about |
Project Idea : A project based on scanning and detecting Aruco codes. Implementing Homography for estimation of intrinsic and extrinsic camera calibration parameters and inclusion of Pose Estimation for the implementation of augmented Reality projects in further future projects. For Qr Code Detection Visit : this link
For more Projects visit : Sahil Khosla
Aruco Codes - AugmentedReality uco Codes
These are the special augmented reality markers which have a unique identification number inside them. These markers are decoded in binary serialization and can be decoded manually as well as by computer also. ArUco marker is a 5x5 grid that is black and white in color. ArUco markers are based on Hamming code. In the grid, the first, third and fifth columns represent parity bits. The second and fourth columns represent the data bits. Hence, there are ten total data bits. So the maximum number of markers that can be encoded are-
2^10 = 1024
The main features of ArUco are:
1. Detect markers with a single line of C++ code.
2. Detect various dictionaries: ARUCO, AprilTag, ArToolKit+, ARTAG, CHILITAGS.
3. Faster than any other library for detection of markers
4. Few dependencies OpenCV (>=2.4.9) and eigen3 (included in the library).
5. Detection of Marker Maps (several markers).
6. Trivial integration with OpenGL and OGRE.
7. Fast, reliable and cross-platform because relies on OpenCV.
8. Examples that will help you to get running your AR application in less than 5 minutes.
9. Calibrate you camera using Aruco ChessBoard
Reference aruco library
Installation
1. Install openCV
2. Install numpy library
3. Install Aruco Library
Make sure you have python installed in ubuntu system
Running the Code
Open terminal and type
->python aruco_poseEstimation.py