A fiducial tag invariant to rotation, translation, and perspective transformations

This work introduces a novel visual fiducial tag appropriate for applications of automatic identification. The proposed tag is based in Order Type, a construction defined in Computational Geometry, which is invariant to 3D translation, rotation, and projective transformations. Three main contributions are presented: first we describe the design of the proposed tags, the procedures for detecting them from an image, and the algorithms for computing an identifier from them. Second, we analyze the feasibility of the proposal in three different conditions of tag's rotation, distance to the tag, and the effect of noise in point positions for the recognition process. Third, we show the applicability of the proposed tags with simulated images. The conducted experiments indicate that the tags are very robust to the image generation process, suitable for automatic identification up to 3472 different tags, and also for the pose estimation in Computer Vision applications.