| 1. |
- Albl, Cenek, et al.
(författare)
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Rolling Shutter Camera Absolute Pose
- 2020
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Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - 0162-8828. ; 42:6, s. 1439-1452
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Tidskriftsartikel (refereegranskat)abstract
- We present minimal, non-iterative solutions to the absolute pose problem for images from rolling shutter cameras. The absolute pose problem is a key problem in computer vision and rolling shutter is present in a vast majority of today's digital cameras. We discuss several camera motion models and propose two feasible rolling shutter camera models for a polynomial solver. In previous work a linearized camera model was used that required an initial estimate of the camera orientation. We show how to simplify the system of equations and make this solver faster. Furthermore, we present a first solution of the non-linearized camera orientation model using the Cayley parameterization. The new solver does not require any initial camera orientation estimate and therefore serves as a standalone solution to the rolling shutter camera pose problem from six 2D-to-3D correspondences. We show that our algorithms outperform P3P followed by a non-linear refinement using a rolling shutter model.
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| 2. |
- Ask, Erik, et al.
(författare)
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Tractable and Reliable Registration of 2D Point Sets
- 2014
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Ingår i: Lecture Notes in Computer Science (Computer Vision - ECCV 2014, 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I). - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783319105895 - 9783319105901 ; 8689, s. 393-406
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Konferensbidrag (refereegranskat)abstract
- This paper introduces two new methods of registering 2D point sets over rigid transformations when the registration error is based on a robust loss function. In contrast to previous work, our methods are guaranteed to compute the optimal transformation, and at the same time, the worst-case running times are bounded by a low-degree polynomial in the number of correspondences. In practical terms, this means that there is no need to resort to ad-hoc procedures such as random sampling or local descent methods that cannot guarantee the quality of their solutions. We have tested the methods in several different settings, in particular, a thorough evaluation on two benchmarks of microscopic images used for histologic analysis of prostate cancer has been performed. Compared to the state-of-the-art, our results show that the methods are both tractable and reliable despite the presence of a significant amount of outliers.
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| 3. |
- Barath, Daniel, et al.
(författare)
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Making Affine Correspondences Work in Camera Geometry Computation
- 2020
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 12356 LNCS, s. 723-740
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Konferensbidrag (refereegranskat)abstract
- Local features e.g. SIFT and its affine and learned variants provide region-to-region rather than point-to-point correspondences. This has recently been exploited to create new minimal solvers for classical problems such as homography, essential and fundamental matrix estimation. The main advantage of such solvers is that their sample size is smaller, e.g., only two instead of four matches are required to estimate a homography. Works proposing such solvers often claim a significant improvement in run-time thanks to fewer RANSAC iterations. We show that this argument is not valid in practice if the solvers are used naively. To overcome this, we propose guidelines for effective use of region-to-region matches in the course of a full model estimation pipeline. We propose a method for refining the local feature geometries by symmetric intensity-based matching, combine uncertainty propagation inside RANSAC with preemptive model verification, show a general scheme for computing uncertainty of minimal solvers results, and adapt the sample cheirality check for homography estimation. Our experiments show that affine solvers can achieve accuracy comparable to point-based solvers at faster run-times when following our guidelines. We make code available at https://github.com/danini/affine-correspondences-for-camera-geometry.
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| 4. |
- Byröd, Martin, et al.
(författare)
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Fast and Robust Numerical Solutions to Minimal Problems for Cameras with Radial Distortion
- 2008
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Ingår i: [Host publication title missing]. ; , s. 2586-2593
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Konferensbidrag (refereegranskat)abstract
- A number of minimal problems of structure from motion for cameras with radial distortion have recently been studied and solved in some cases. These problems are known to be numerically very challenging and in several cases there exist no known practical algorithm yielding solutions in floating point arithmetic. We make some crucial observations concerning the floating point implementation of Gröbner basis computations and use these new insights to formulate fast and stable algorithms for two minimal problems with radial distortion previously solved in exact rational arithmetic only: (i) simultaneous estimation of essential matrix and a common radial distortion parameter for two partially calibrated views and six image point correspondences and (ii) estimation of fundamental matrix and two different radial distortion parameters for two uncalibrated views and nine image point correspondences. We demonstrate on simulated and real experiments that these two problems can be efficiently solved in floating point arithmetic.
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| 5. |
- Cornelius, Hugo, et al.
(författare)
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Towards complete free-form reconstruction of complex 3D scenes from an unordered set of uncalibrated images
- 2004
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Ingår i: STATISTICAL METHODS IN VIDEO PROCESSING. - BERLIN : SPRINGER. - 3540239898 ; , s. 1-12
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Konferensbidrag (refereegranskat)abstract
- This paper describes a method for accurate dense reconstruction of a complex scene from a small set of high-resolution unorganized still images taken by a hand-held digital camera. A fully automatic data processing pipeline is proposed. Highly discriminative features are first detected in all images. Correspondences are then found in all image pairs by wide-baseline stereo matching and used in a scene structure and camera reconstruction step that can cope with occlusion and outliers. Image pairs suitable for dense matching are automatically selected, rectified and used in dense binocular matching. The dense point cloud obtained as the union of all pairwise reconstructions is fused by local approximation using oriented geometric primitives. For texturing, every primitive is mapped on the image with the best resolution. The global structure reconstruction in the first step allows us to work with an unorganized set of images and to avoid error accumulation. By using object-centered geometric primitives we are able to preserve the flexibility of the method to describe complex free-form structures, preserve the possibility to build the dense model in an incremental way, and to retain the possibility to refine the cameras and the dense model by bundle adjustment. Results are demonstrated on partial models of a circular church and a Henri de Miller's sculpture. We observed spatial resolution in the range of centimeters on objects of about 20 m in size.
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| 6. |
- Duff, Timothy, et al.
(författare)
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PL1 P - Point-Line Minimal Problems Under Partial Visibility in Three Views
- 2020
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Ingår i: Computer Vision – ECCV 2020. - Cham : Springer Nature. ; , s. 175-192
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Konferensbidrag (refereegranskat)abstract
- We present a complete classification of minimal problems for generic arrangements of points and lines in space observed partially by three calibrated perspective cameras when each line is incident to at most one point. This is a large class of interesting minimal problems that allows missing observations in images due to occlusions and missed detections. There is an infinite number of such minimal problems; however, we show that they can be reduced to 140616 equivalence classes by removing superfluous features and relabeling the cameras. We also introduce camera-minimal problems, which are practical for designing minimal solvers, and show how to pick a simplest camera-minimal problem for each minimal problem. This simplification results in 74575 equivalence classes. Only 76 of these were known; the rest are new. To identify problems having potential for practical solving of image matching and 3D reconstruction, we present several natural subfamilies of camera-minimal problems as well as compute solution counts for all camera-minimal problems which have less than 300 solutions for generic data.
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| 7. |
- Duff, Timothy, et al.
(författare)
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PLMP : Point-Line Minimal Problems in Complete Multi-View Visibility
- 2024
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Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - : Institute of Electrical and Electronics Engineers (IEEE). - 0162-8828 .- 1939-3539. ; 46:1, s. 421-435
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Tidskriftsartikel (refereegranskat)abstract
- We present a complete classification of all minimal problems for generic arrangements of points and lines completely observed by calibrated perspective cameras. We show that there are only 30 minimal problems in total, no problems exist for more than 6 cameras, for more than 5 points, and for more than 6 lines. We present a sequence of tests for detecting minimality starting with counting degrees of freedom and ending with full symbolic and numeric verification of representative examples. For all minimal problems discovered, we present their algebraic degrees, i.e.the number of solutions, which measure their intrinsic difficulty. It shows how exactly the difficulty of problems grows with the number of views. Importantly, several new minimal problems have small degrees that might be practical in image matching and 3D reconstruction.
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| 8. |
- Dusmanu, Mihai, et al.
(författare)
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D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
- 2019
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Ingår i: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. - 1063-6919. ; 2019-June, s. 8084-8093
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Konferensbidrag (refereegranskat)abstract
- In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions. We propose an approach where a single convolutional neural network plays a dual role: It is simultaneously a dense feature descriptor and a feature detector. By postponing the detection to a later stage, the obtained keypoints are more stable than their traditional counterparts based on early detection of low-level structures. We show that this model can be trained using pixel correspondences extracted from readily available large-scale SfM reconstructions, without any further annotations. The proposed method obtains state-of-the-art performance on both the difficult Aachen Day-Night localization dataset and the InLoc indoor localization benchmark, as well as competitive performance on other benchmarks for image matching and 3D reconstruction.
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| 9. |
- Hruby, Petr, et al.
(författare)
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Four-view Geometry with Unknown Radial Distortion
- 2023
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Ingår i: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. - 9798350301298 ; , s. 8990-9000
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Konferensbidrag (refereegranskat)abstract
- We present novel solutions to previously unsolved prob-lems of relative pose estimation from images whose calibration parameters, namely focal lengths and radial distortion, are unknown. Our approach enables metric reconstruction without modeling these parameters. The minimal case for reconstruction requires 13 points in 4 views for both the calibrated and uncalibrated cameras. We describe and implement the first solution to these minimal problems. In the calibrated case, this may be modeled as a polynomial sys-tem of equations with 3584 solutions. Despite the apparent intractability, the problem decomposes spectacularly. Each solution falls into a Euclidean symmetry class of size 16, and we can estimate 224 class representatives by solving a sequence of three subproblems with 28, 2, and 4 solutions. We highlight the relationship between internal constraints on the radial quadrifocal tensor and the relations among the principal minors of a 4× 4 matrix. We also address the case of 4 upright cameras, where 7 points are minimal. Finally, we evaluate our approach on simulated and real data and benchmark against previous calibration-free solutions, and show that our method provides an efficient startup for an SfM pipeline with radial cameras.
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| 10. |
- Kukelova, Zuzana, et al.
(författare)
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Fast and Robust Numerical Solutions to Minimal Problems for Cameras with Radial Distortion
- 2010
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Ingår i: Computer Vision and Image Understanding. - : Elsevier BV. - 1077-3142. ; 114:2, s. 234-244
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Tidskriftsartikel (refereegranskat)abstract
- A number of minimal problems of structure from motion for cameras with radial distortion have recently been studied and solved in some cases. These problems are known to be numerically very challenging and in several cases there were no practical algorithms yielding solutions in floating point arithmetic. We make some crucial observations concerning the floating point implementation of Gröbner basis computations and use these new insights to formulate fast and stable algorithms for two minimal problems with radial distortion previously solved in exact rational arithmetic only: (i) simultaneous estimation of essential matrix and a common radial distortion parameter for two partially calibrated views and six image point correspondences and (ii) estimation of fundamental matrix and two different radial distortion parameters for two uncalibrated views and nine image point correspondences. We demonstrate that these two problems can be efficiently solved in floating point arithmetic in simulated and real experiments. For comparison we have also invented a new non-minimal algorithm for estimating fundamental matrix and two different radial distortion parameters for two uncalibrated views and twelve image point correspondences based on a generalized eigenvalue problem.
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