This paper presents random dot markers (RDM) printed on transparent sheets as transparent fiducial markers. They are extremely unobstructive, and useful for developing novel user interfaces. However, the marker identification is required to be robust to observable back sides of the transparent sheets. To realize such markers, we propose a graph based framework for geometric feature based robust point matching for RDM. 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.