Wide-angle visual feature matching for outdoor localization
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.
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|Item Type:||Journal Article|
|Keywords:||features, keypoints, scale-space, matching, wide-angle , fisheye, catadioptric, spherical diffusion, visual odometry, place recognition|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
Past > Schools > School of Engineering Systems
|Deposited On:||18 Aug 2010 14:21|
|Last Modified:||01 Mar 2012 00:06|
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