Scale-Invariant Features on the Sphere

This paper considers an application of scale-invariant feature detection using scale-space analysis suitable for use with wide field of view cameras. Rather than obtain scalespace images via convolution with the Gaussian function on the image plane, we map the image to the sphere and obtain scale-space images as the solution to the heat (diffusion) equation on the sphere which is implemented in the frequency domain using spherical harmonics. The percentage correlation of scale-invariant features that may be matched between any two wide-angle images subject to change in camera pose is then compared using each of these methods. We also present a means by which the required sampling bandwidth may be determined and propose a suitable anti-aliasing filter which may be used when this bandwidth exceeds the maximum permissible due to computational requirements. The results show improved performance using scale-space images obtained as the solution of the diffusion equation on the sphere, wi...

• Type: Conference
• Year: 2007
• Where: ICCV
• Authors: Peter Hansen, Peter Corke, Wageeh Boles, Kostas Daniilidis
• Keywords: Anti-aliasing filter, Computer Vision, ICCV 2007, Scale-invariant Features, Scale-space Images