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arXiv Computer Vision By James Pritts, Till Sittart, Hendrik Sauer, Silja Jan{\ss}en, Felix Seegr\"aber, David Nakath, Kevin K\"oser

BlobBoards: Robust Markers for Accurate Pose

Read the original on arXiv Computer Vision →

BlobBoards is a fiducial marker system that uses a dense, multi‑scale field of Gaussian blobs and a feature‑based pipeline for joint detection, identification, and pose estimation. The system registers each board from hundreds of blob features, leveraging dense spatial coverage and multiple scales to maintain detectability across large changes in focal length, distance, and obliquity. Compared to state‑of‑the‑art tags, BlobBoards achieves superior detection rates, lower median translation errors, and greater robustness to occlusion, with significant reductions in pose errors and large‑rotation failures.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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