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Robust Feature Extraction and Matching for Omnidirectional Images

  • Davide Scaramuzza
  • Nicolas Criblez
  • Agostino Martinelli
  • Roland Siegwart
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 42)

Summary

This paper presents a new and robust method for extracting and matching visual vertical features between images taken by an omnidirectional camera. Matching robustness is achieved by creating a descriptor which is unique and distinctive for each feature. Furthermore, the proposed descriptor is invariant to rotation. The robustness of the approach is validated through real experiments with a wheeled robot equipped with an omnidirectional camera. We show that vertical lines are very well extracted and tracked during the robot motion. At the end, we also present an application of our algorithm to the robot simultaneous localization and mapping in an unknown environment.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Davide Scaramuzza
    • 1
  • Nicolas Criblez
    • 2
  • Agostino Martinelli
    • 3
  • Roland Siegwart
    • 1
  1. 1.Swiss Federal Institute of Technology Zurich 
  2. 2.Swiss Federal Institute of Technology Lausanne 
  3. 3.INRIA 

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