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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}
}
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