Hashem Tamimi, Henrik Andreasson, André Treptow, Tom Duckett and Andreas Zell
Localization of mobile robots with omnidirectional vision using Particle Filter and Iterative SIFT
Robotics and Autonomous Systems, Volume 54, Issue 9, 31 September 2006, pp. 758-765
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.
Download:
Paper: [PDF (1.4MB)]
Bibtex:
@ARTICLE{Andreasson_etal:RAS:2007,
  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},
  JOURNAL = {Robotics and Autonomous Systems},
  YEAR = {2006},
  VOLUME = {54},
  NUMBER = {9},
  PAGES = {758--765},
  ISSN = {0921-8890},
  MONTH = {September}
}