Wide-angle Visual Feature Matching for Outdoor Localization

  • Authors:

  • Peter Hansen;Peter Corke;Wageeh Boles

  • Affiliations:

  • Queensland University of Technology, Brisbane, Australia,;CSIRO ICT Centre, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia,

  • Venue:
  • International Journal of Robotics Research
  • Year:
  • 2010

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Abstract

Wide-angle images exhibit significant distortion for which existing scale-space detectors such as the scale-invariant feature transform (SIFT) are inappropriate. The required scale-space images for feature detection are correctly obtained through the convolution of the image, mapped to the sphere, with the spherical Gaussian. A new visual key-point detector, based on this principle, is developed and several computational approaches to the convolution are investigated in both the spatial and frequency domain. In particular, a close approximation is developed that has comparable computation time to conventional SIFT but with improved matching performance. Results are presented for monocular wide-angle outdoor image sequences obtained using fisheye and equiangular catadioptric cameras. We evaluate the overall matching performance (recall versus 1-precision) of these methods compared to conventional SIFT. We also demonstrate the use of the technique for variable frame-rate visual odometry and its application to place recognition.