ArUcOmni: Detection of Highly Reliable Fiducial Markers in Panoramic Images - Crossminds
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ArUcOmni: Detection of Highly Reliable Fiducial Markers in Panoramic Images
Sep 29, 2020
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Authors: Jaouad Hajjami, Jordan Caracotte, Guillaume Caron, Thibault Napoléon Description: In this paper, we propose an adaptation of marker detection algorithm for panoramic cameras such as catadioptric and fisheye sensors. Due to distortions and non-uniform resolution of such sensors, the methods that are commonly used in perspective images cannot be applied directly. This work is in contrast with the existing marker detection framework: Automatic reliable fiducial markers Under occlusion (ArUco) for a conventional camera. To keep the same performance for panoramic cameras, our method is based on a spherical representation of the image that allows the marker to be detected and to estimate its 3D pose. We evaluate our approach on a new shared dataset that consists of a 3D rig of markers taken with two different sensors: a catadioptric camera and a fisheye camera. The evaluation has been performed against ArUco algorithm without rectification and with one of the rectified approaches based on the fisheye model.
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