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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sweeney, C. Kneip, L. Hollerer, T. Turk, M. |
| Copyright Year | 2015 |
| Description | Author affiliation: Univ. of California Santa Barbara, Santa Barbara, CA, USA (Sweeney, C.; Hollerer, T.; Turk, M.) || Res. Sch. of Eng., Australian Nat. Univ., Canberra, ACT, Australia (Kneip, L.) |
| Abstract | We propose a novel solution for computing the relative pose between two generalized cameras that includes reconciling the internal scale of the generalized cameras. This approach can be used to compute a similarity transformation between two coordinate systems, making it useful for loop closure in visual odometry and registering multiple structure from motion reconstructions together. In contrast to alternative similarity transformation methods, our approach uses 2D-2D image correspondences thus is not subject to the depth uncertainty that often arises with 3D points. We utilize a known vertical direction (which may be easily obtained from IMU data or vertical vanishing point detection) of the generalized cameras to solve the generalized relative pose and scale problem as an efficient Quadratic Eigenvalue Problem. To our knowledge, this is the first method for computing similarity transformations that does not require any 3D information. Our experiments on synthetic and real data demonstrate that this leads to improved performance compared to methods that use 3D-3D or 2D-3D correspondences, especially as the depth of the scene increases. |
| Starting Page | 3305 |
| Ending Page | 3313 |
| File Size | 578249 |
| Page Count | 9 |
| File Format | |
| ISSN | 10636919 |
| e-ISBN | 9781467369640 |
| DOI | 10.1109/CVPR.2015.7298951 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-07 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Cameras Three-dimensional displays Eigenvalues and eigenfunctions Noise Accuracy Uncertainty Calibration |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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