NDLI: RUNE-Tag: A high accuracy fiducial marker with strong occlusion resilience

Content Provider	IEEE Xplore Digital Library
Author	Bergamasco, F. Albarelli, A. Rodola, E. Torsello, A.
Copyright Year	2011
Description	Author affiliation: Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca' Foscari Venezia - via Torino, 155 - 30172 Venice Italy (Bergamasco, F.; Albarelli, A.; Rodola, E.; Torsello, A.)
Abstract	Over the last decades fiducial markers have provided widely adopted tools to add reliable model-based features into an otherwise general scene. Given their central role in many computer vision tasks, countless different solutions have been proposed in the literature. Some designs are focused on the accuracy of the recovered camera pose with respect to the tag; some other concentrate on reaching high detection speed or on recognizing a large number of distinct markers in the scene. In such a crowded area both the researcher and the practitioner are licensed to wonder if there is any need to introduce yet another approach. Nevertheless, with this paper, we would like to present a general purpose fiducial marker system that can be deemed to add some valuable features to the pack. Specifically, by exploiting the projective properties of a circular set of sizeable dots, we propose a detection algorithm that is highly accurate. Further, applying a dot pattern scheme derived from error-correcting codes, allows for robustness with respect to very large occlusions. In addition, the design of the marker itself is flexible enough to accommodate different requirements in terms of pose accuracy and number of patterns. The overall performance of the marker system is evaluated in an extensive experimental section, where a comparison with a well-known baseline technique is presented.
Starting Page	113
Ending Page	120
File Size	3960039
Page Count	8
File Format	PDF
ISBN	9781457703942
ISSN	10636919
e-ISBN	9781457703959
DOI	10.1109/CVPR.2011.5995544
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Polynomials Accuracy Estimation Robustness Generators Encoding
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Rune-tag: A high accuracy fiducial marker with strong occlusion resilience (2011)

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RUNE-Tag: A high accuracy fiducial marker with strong occlusion resilience

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RUNE-Tag: A high accuracy fiducial marker with strong occlusion resilience