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.
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Labrosse, F.: Short and long-range visual navigation using warped panoramic images. Robotics and Autonomous Systems 55(9), 675–684 (2007)
Labrosse, F.: The visual compass: Performance and limitations of an appearance-based method. Journal of Field Robotics 23(10), 913–941 (2006)
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© 2012 Springer-Verlag Berlin Heidelberg
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Cao, J., Labrosse, F., Dee, H. (2012). A Novel Image Similarity Measure for Place Recognition in Visual Robotic Navigation. In: Herrmann, G., et al. Advances in Autonomous Robotics. TAROS 2012. Lecture Notes in Computer Science(), vol 7429. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32527-4_37
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DOI: https://doi.org/10.1007/978-3-642-32527-4_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32526-7
Online ISBN: 978-3-642-32527-4
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