Condition-invariant, top-down visual place recognition

@article{Milford2014ConditioninvariantTV,
  title={Condition-invariant, top-down visual place recognition},
  author={Michael Milford and Walter J. Scheirer and Eleonora Vig and Arren J. Glover and Oliver Baumann and Jason B. Mattingley and David D. Cox},
  journal={2014 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2014},
  pages={5571-5577}
}
In this paper we present a novel, condition-invariant place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images, alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We conduct an… CONTINUE READING
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Key Quantitative Results

  • We achieve recall rates of up to 51% at 100% precision, matching places that have undergone drastic perceptual change while rejecting match hypotheses between highly aliased images of different places.

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