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A Novel Image Similarity Measure for Place Recognition in Visual Robotic Navigation

  • Juan Cao
  • Frédéric Labrosse
  • Hannah Dee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7429)

Abstract

In this work we tackle the issue of visually recognising a place without any prior knowledge of its position, even in a world where the same place can look different or many places can look identical.

To achieve a fast and robust image similarity measure for place recognition, we use the concept of quadtree decomposition combined with a number of standard image distance measures to create a novel image similarity method. Unlike the majority of current image comparison methods that use feature extraction and matching, our approach is a direct pixel-wise comparison of two images [1] gaining robustness through the incorporation of the quadtree concept. Quadtrees not only provide a noise resistant, fast, and easy to use comparison method, but also allow us to identify those image regions that genuinely represent changes within the environment.

Keywords

Similarity Measure Image Pair Image Similarity Pinch Point Place Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Labrosse, F.: Short and long-range visual navigation using warped panoramic images. Robotics and Autonomous Systems 55(9), 675–684 (2007)CrossRefGoogle Scholar
  2. 2.
    Labrosse, F.: The visual compass: Performance and limitations of an appearance-based method. Journal of Field Robotics 23(10), 913–941 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Juan Cao
    • 1
  • Frédéric Labrosse
    • 1
  • Hannah Dee
    • 1
  1. 1.Department of Computer ScienceAberystwyth UniversityUnited Kingdom

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