Hashem Tamimi, Henrik Andreasson, André Treptow, Tom Duckett and Andreas Zell
Localization of Mobile Robots with Omnidirectional Vision using Particle Filter and Iterative SIFT
Proc. European Conference on Mobile Robots (ECMR), 2005, pp. 2-7
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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@INPROCEEDINGS{Tamimi_etal:ECMR:2005,
  AUTHOR = {Tamimi, Hashem and Andreasson, Henrik and Treptow, Andr\'{e} and Duckett, Tom and Zell Andreas},
  TITLE = {Localization of Mobile Robots with Omnidirectional Vision using Particle Filter and Iterative SIFT},
  BOOKTITLE = {Proceedings of the European Conference on Mobile Robots (ECMR)},
  YEAR = {2005},
  DATE = {September, 7--10},
  ADRESS = {Ancona, Italy},
  PAGES = {2--7}
}