Hashem Tamimi, Henrik Andreasson, André Treptow, Tom Duckett and Andreas Zell

Localization of Mobile Robots with Omnidirectional Vision using Particle Filter and Iterative SIFT

In Proc. of the European Conference on Mobile Robots (ECMR05)



Abstract

The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense,
especially when dealing with omnidirectional vision. In this work, we propose a new approach that reduces the number of features generated by SIFT as well as their extraction and matching time.
With the help of a particle filter, we demonstrate that we can still localize the mobile robot accurately with a lower number of features.

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Bibtex

@INPROCEEDINGS{Tamimi05,
AUTHOR = "Hashem {Tamimi} and Henrik {Andreasson} and Andr\'{e} {Treptow} and Tom {Duckett} and Andreas {Zell}",
TITLE = "Localization of Mobile Robots with Omnidirectional Vision using Particle Filter and Iterative SIFT",
BOOKTITLE = "Proceedings of the 2005 European Conference on Mobile Robots (ECMR05)",
PAGES= "1--7"
ADDRESS = "Ancona, Italy",
YEAR = "2005"
}