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Topological SLAM Using Omnidirectional Images: Merging Feature Detectors and Graph-Matching

  • Anna Romero
  • Miguel Cazorla
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6474)

Abstract

Image feature extraction and matching is useful in many areas of robotics such as object and scene recognition, autonomous navigation, SLAM and so on. This paper describes a new approach to the problem of matching features and its application to scene recognition and topological SLAM. For that purpose we propose a prior image segmentation into regions in order to group the extracted features in a graph so that each graph defines a single region of the image. This image segmentation considers that the left part of the image is the continuation of the right part. The matching process will take into account the features and the structure (graph) using the GTM algorithm. Then, using this method of comparing images, we propose an algorithm for constructing topological maps. During the experimentation phase we will test the robustness of the method and its ability constructing topological maps. We have also introduced a new hysteresis behavior in order to solve some problems found in construction of the graph.

Keywords

Topological Mapping Graph matching Visual features 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Anna Romero
    • 1
  • Miguel Cazorla
    • 1
  1. 1.Instituto Universitario Investigación en InformáticaAlicanteSpain

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