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Carnegie Mellon Robotics Institute

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Abstract

Fast pattern detection and identification is a fundamental problem for many applications of real-time vision systems. The desirable characteristics for a solution are that it takes little computation, localizes a pattern robustly and with high accuracy, and can identify a large number of unique pattern identifiers so that many patterns can be tracked within a field a view. We will present a system that can accurately track a broad class of patterns both accurately and quickly, when using a suitable low level vision system that can return calibrated coordinates of regions in a image. Both pattern design and the detection algorithm are considered together to find a solution meeting the above criteria. Along the way, assumptions are verified to make informed choices without relying on guesswork, and allowing similar systems to be designed on a solid experimental and statistical basis.

Notes

Associated Lab(s) / Group(s): MultiRobot Lab

Associated Project(s): Robotic Soccer

Number of pages: 6

Text Reference

James Bruce and Manuela Veloso, "Fast and accurate vision-based pattern detection and identification," Proceedings of ICRA-03, the 2003 IEEE International Conference on Robotics and Automation (ICRA '03), May, 2003.

BibTeX Reference

@inproceedings{Veloso_2003_4400,
   author = "James Bruce and Manuela Veloso",
   title = "Fast and accurate vision-based pattern detection and identification",
   booktitle = "Proceedings of ICRA-03, the 2003 IEEE International Conference on Robotics and Automation (ICRA '03)",
   month = "May",
   year = "2003",
}

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