| 1. |
- Fredriksson, Johan, et al.
(författare)
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Fast and Reliable Two-View Translation Estimation
- 2014
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Ingår i: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. - 1063-6919. - 9781479951178 ; , s. 1606-1612
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Konferensbidrag (refereegranskat)abstract
- It has long been recognized that one of the fundamental difficulties in the estimation of two-view epipolar geometry is the capability of handling outliers. In this paper, we develop a fast and tractable algorithm that maximizes the number of inliers under the assumption of a purely translating camera. Compared to classical random sampling methods, our approach is guaranteed to compute the optimal solution of a cost function based on reprojection errors and it has better time complexity. The performance is in fact independent of the inlier/outlier ratio of the data. This opens up for a more reliable approach to robust ego-motion estimation. Our basic translation estimator can be embedded into a system that computes the full camera rotation. We demonstrate the applicability in several difficult settings with large amounts of outliers. It turns out to be particularly well-suited for small rotations and rotations around a known axis (which is the case for cellular phones where the gravitation axis can be measured). Experimental results show that compared to standard RANSAC methods based on minimal solvers, our algorithm produces more accurate estimates in the presence of large outlier ratios.
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| 2. |
- Svärm, Linus, et al.
(författare)
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Accurate Localization and Pose Estimation for Large 3D Models
- 2014
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Ingår i: Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. - 1063-6919. - 9781479951178 ; , s. 532-539
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Konferensbidrag (refereegranskat)abstract
- We consider the problem of localizing a novel image in a large 3D model. In principle, this is just an instance of camera pose estimation, but the scale introduces some challenging problems. For one, it makes the correspondence problem very difficult and it is likely that there will be a significant rate of outliers to handle. In this paper we use recent theoretical as well as technical advances to tackle these problems. Many modern cameras and phones have gravitational sensors that allow us to reduce the search space. Further, there are new techniques to efficiently and reliably deal with extreme rates of outliers. We extend these methods to camera pose estimation by using accurate approximations and fast polynomial solvers. Experimental results are given demonstrating that it is possible to reliably estimate the camera pose despite more than 99% of outlier correspondences.
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| 3. |
- Svärm, Linus, et al.
(författare)
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Improving Robustness for Inter-Subject Medical Image Registration Using a Feature-Based Approach
- 2015
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Ingår i: Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on. ; , s. 824-828
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Konferensbidrag (refereegranskat)abstract
- We propose new feature-based methods for rigid and affine image registration. These are compared to state-of-the-art intensity-based techniques as well as existing feature-based methods. On challenging datasets of brain MR and whole-body CT images, a significant improvement in terms of speed, robustness to outlier structures and dependence on initialization is shown.
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