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ARTag, a Fiducial Marker System Using Digital Techniques
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.
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Cited by
AprilTag: A robust and flexible visual fiducial system
Olson, E. (2011) · 2011 IEEE International Conference on Robotics and Automation · doi:10.1109/icra.2011.5979561 · Cited by 1,770
Pose estimation for augmented reality: a hands-on survey
Marchand, E., Uchiyama, H., & Spindler, F. (2016) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2015.2513408 · Cited by 746
A survey of visual, mixed, and augmented reality gaming
Thomas, B. H. (2012) · Computers in Entertainment · doi:10.1145/2381876.2381879 · Cited by 128
Metadata
- Authors
- Fiala, M.
- Venue
- 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)
- Publisher
- IEEE
- Published
- 2005-07-27
- Volume
- 2
- Pages
- 590-596
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2164139712
- Cited by
- 860
- References
- 0
- FWCI
- 25.72
- Type
- conference paper
- Language
- en
- Open access
- closed
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