ARTag, a Fiducial Marker System Using Digital Techniques

TLDR

Fiducial marker systems provide automatically detectable patterns for pose estimation in AR, robotics, and related applications, with key performance metrics including false positive and confusion rates, minimum marker size, and robustness to lighting changes. ARTag achieves low false positives and confusion rates by employing digital coding theory, edge linking for lighting immunity, and bi‑tonal planar patterns that encode a unique ID with checksums and forward error correction. Experiments show ARTag’s error rates are very low, it operates without a gray‑scale threshold, and it can encode up to 2002 unique IDs, demonstrating its effectiveness.

Abstract

Fiducial marker systems consist of patterns that are mounted in the environment and automatically detected in digital camera images using an accompanying detection algorithm. They are useful for augmented reality (AR), robot navigation, and general applications where the relative pose between a camera and object is required. Important parameters for such marker systems is their false detection rate (false positive rate), their inter-marker confusion rate, minimal detection size (in pixels) and immunity to lighting variation. ARTag is a marker system that uses digital coding theory to get a very low false positive and inter-marker confusion rate with a small required marker size, employing an edge linking method to give robust lighting variation immunity. ARTag markers are bi-tonal planar patterns containing a unique ID number encoded with robust digital techniques of checksums and forward error correction (FEC). This proposed new system, ARTag has very low and numerically quantifiable error rates, does not require a grey scale threshold as does other marker systems, and can encode up to 2002 different unique ID's with no need to store patterns. Experimental results are shown validating this system.