We are seeking potential collaborators who have some ideas to use our markers for making nice applications such as entertainment, education, etc.
If you have any ideas, please contact me (oyamada@tottori-u.ac.jp) !!
This paper presents random dot markers printed on transparent sheets as transparent fiducial markers. They are extremely unobstructive, and useful for novel user interfaces. However, the marker identification is required to be robust to observable backgrounds of the transparent sheets. To realize such markers, we propose a graph based framework for geometric feature based robust point matching between two sets of points. Instead of building one-to-one correspondences, we first build one-to-many correspondences using a 2D affinity matrix, and then globally optimize the matching assignment from the matrix. Especially, we incorporate pairwise relationship between neighboring points using local geometric descriptors into the matrix, and finally solve it with spectral matching. In the evaluation, we investigate the effectiveness of the global assignment from one-to-many correspondences, and finally show that our proposed method is enough robust to identifying overlapped markers.
This work was partially supported by JSPS KAKENHI Grant Number JP16K16087.
C++ code with calibration example is on my gitlab repository.