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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Falcon-Morales, L. Bayro-Corrochano, L.E. |
| Copyright Year | 2008 |
| Description | Author affiliation: Tecnol. de Monterrey, Monterrey (Falcon-Morales, L.) || CINVESTAV, Unidad Guadalajara, Guadalajara (Bayro-Corrochano, L.E.) |
| Abstract | In this paper we apply the classic theory of harmonic analysis and the conformal geometric algebra (CGA) to evaluate the Fourier transform on the unit sphere $S^{2}$ and on the rotation group SO(3). Since the images taken by omnidirectional sensors can be mapped to the sphere, the problem of attitude estimation of a 3D camera rotation can be treated as a problem of estimating rotations between spherical images. Usually, this rotation estimation problem has been solved using the Radon transform with point correlation or with line correlation. Using a catadioptric system with a parabolic mirror, 3D lines will be projected as great circles on $S^{2}$ and then projected as circles on the image plane. CGA is a mathematical framework where its basic entities, spheres, circles, lines and planes can be used with incidence algebra operations to improve the line correlation in the Radon transform as a dual-circle correlation. Thus, harmonic analysis theory and conformal geometric algebra will be joined in this paper to improve the search of a 3D rotation correspondence between two omnidirectional images. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 308119 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424421749 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2008.4761341 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-08 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algebra Harmonic analysis Fourier transforms Cameras Mirrors Mobile robots Argon Image sensors Computer vision Computational efficiency |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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