Detection of CCTag markers made up of concentric circles. Implementations in both CPU and GPU.
See paper: "Detection and Accurate Localization of Circular Fiducials under Highly Challenging Conditions." Lilian Calvet, Pierre Gurdjos, Carsten Griwodz and Simone Gasparini. CVPR 2016.
Markers to print are located here.
WARNING Please respect the provided margins. The reported detection rate and localization accuracy are valid with completely planar support: be careful not to use bent support (e.g. corrugated sheet of paper).
The four rings CCTags will be available soon.
CCTags requires either CUDA 8.0 and newer or CUDA 7.0 (CUDA 7.5 builds are known to have runtime errors on some devices including the GTX980Ti). The device must have at least compute capability 3.5.
Check your graphic card CUDA compatibility here.
See BUILD text file.
Continuous integration:
Once compiled, you might want to run the CCTag detection on a sample image:
$ build/src/detection -n 3 -i sample/01.png
For the library interface, see ICCTag.hpp.
CCTag is licensed under MPL v2 license.
Lilian Calvet (CPU, lilian.calvet@gmail.com)
Carsten Griwodz (GPU, griff@simula.no)
Stian Vrba (CPU, vrba@mixedrealities.no)
Cyril Pichard (pih@mikrosimage.eu)
This has been developed in the context of the European project POPART founded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 644874.
Additional contributions for performance optimizations have been funded by the Norwegian RCN FORNY2020 project FLEXCAM.