Title
Scale space for central catadioptric systems: Towards a generic camera feature extractor
Abstract
In this paper we propose a new approach to compute the scale space of any omnidirectional image acquired with a central catadioptric system. When these cameras are central they are explained using the sphere camera model, which unifies in a single model, conventional, paracatadioptric and hypercatadioptric systems. Scale space is essential in the detection and matching of interest points, in particular scale invariant points based on Laplacian of Gaussians, like the well known SIFT. We combine the sphere camera model and the partial differential equations framework on manifolds, to compute the Laplace-Beltrami (LB) operator which is a second order differential operator required to perform the Gaussian smoothing on catadioptric images. We perform experiments with synthetic and real images to validate the generalization of our approach to any central catadioptric system.
Year
DOI
Venue
2011
10.1109/ICCV.2011.6126420
Computer Vision
Keywords
DocType
Volume
Gaussian processes,feature extraction,image matching,smoothing methods,Gaussian smoothing,Gaussians,Laplace-Beltrami operator,Laplacian,central catadioptric system,generic camera feature extractor,hypercatadioptric system,interest point detection,interest point matching,omnidirectional image,paracatadioptric system,partial differential equations framework,scale invariant points,scale space,second order differential operator,sphere camera model
Conference
2011
Issue
ISSN
ISBN
1
1550-5499
978-1-4577-1101-5
Citations 
PageRank 
References 
14
0.67
12
Authors
2
Name
Order
Citations
PageRank
Luis Puig1644.15
J. J. Guerrero213410.02