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TRPLP – Trifocal Relative Pose From Lines at Points
- Source :
- CVPR 2020-IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020-IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun 2020, Seattle / Virtual, United States. pp.12070-12080, ⟨10.1109/CVPR42600.2020.01209⟩, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), CVPR
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
Abstract
- Code available at http://github.com/rfabbri/minus; International audience; We present a method for solving two minimal problems for relative camera pose estimation from three views, which are based on three view correspondences of (i) three points and one line and (ii) three points and two lines through two of the points. These problems are too difficult to be efficiently solved by the state of the art Grobner basis methods. Our method is based on a new efficient homotopy continuation (HC) solver, which dramatically speeds up previous HC solving by specializing HC methods to generic cases of our problems. We show in simulated experiments that our solvers are numerically robust and stable under image noise. We show in real experiment that (i) SIFT features provide good enough point-and-line correspondences for three-view reconstruction and (ii) that we can solve difficult cases with too few or too noisy tentative matches where the state of the art structure from motion initialization fails.
- Subjects :
- Relative camera
Computer science
Grobner basis methods
Feature extraction
Scale-invariant feature transform
Initialization
Geometry
010103 numerical & computational mathematics
02 engineering and technology
Iterative reconstruction
Simulated experiments
01 natural sciences
Relative camera pose estimation
Point-and-line correspondences
0202 electrical engineering, electronic engineering, information engineering
Structure from motion
Three-view reconstruction
TRPLP
0101 mathematics
Pose
Pose estimation
Pipelines
[INFO.INFO-SC]Computer Science [cs]/Symbolic Computation [cs.SC]
Image matching
Minimal problems
business.industry
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Solver
Cameras
Homotopy continuation
SIFT features
HC methods
Generic cases
View correspondences
Efficient homotopy continuation solver
Line (geometry)
Image reconstruction
Three-dimensional displays
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
business
Algorithm
Subjects
Details
- Language :
- English
- ISBN :
- 978-1-72817-168-5
- ISBNs :
- 9781728171685
- Database :
- OpenAIRE
- Journal :
- CVPR 2020-IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020-IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun 2020, Seattle / Virtual, United States. pp.12070-12080, ⟨10.1109/CVPR42600.2020.01209⟩, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), CVPR
- Accession number :
- edsair.doi.dedup.....f1b4e16d363ff3db852e9ca9f50a34d7
- Full Text :
- https://doi.org/10.1109/CVPR42600.2020.01209⟩