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Efficient and Effective Matching of Image Sequences Under Substantial Appearance Changes Exploiting GPS Priors
Olga Vysotska, Tayyab Naseer, Luciano Spinello, Wolfram Burgard, Cyrill Stachniss
Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)
2015
vysotska15icra.pdf



Notes:
The ability to localize a robot is an important capability and matching of observations under substantial changes is a prerequisite for robust long-term operation. This paper investigates the problem of efficiently coping with seasonal changes in image data. We present an extension of a recent approach [15] to visual image matching using sequence information. Our extension allows for exploiting GPS priors in the matching process to overcome the main computational bottleneck of the previous method and to handle loops within the image sequences. We present an experimental evaluation using real world data containing substantial seasonal changes and show that our approach outperforms the previous method in case a noisy GPS pose prior is available.


BibTeX:
@inproceedings{vysotska15icra,
  author = {Olga Vysotska, Tayyab Naseer, Luciano Spinello, Wolfram Burgard, and Cyrill Stachniss},
  title = {Efficient and Effective Matching of Image Sequences Under Substantial Appearance Changes Exploiting GPS Priors},
  booktitle = {Proc.~of the IEEE Int.~Conf.~on Robotics \&
Automation (ICRA)},
  year = 2015,
  url = {http://www2.informatik.uni-freiburg.de/~naseer/publications/vysotska15icra.pdf},
  address = {Seattle}
}