Back to Search
Start Over
Generalized Thin-Plate Spline Warps
- Source :
- 2007 IEEE Conference on Computer Vision and Pattern Recognition ; ISBN: 1-4244-1179-3, International Conference on Computer Vision and Pattern Recognition (CVPR 2007), International Conference on Computer Vision and Pattern Recognition (CVPR 2007), Jun 2007, Minneapolis, United States. ⟨10.1109/CVPR.2007.382998⟩, CVPR'07-Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Minneapolis, USA, International Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2007, Minneapolis, United States, CVPR
- Publication Year :
- 2007
- Publisher :
- HAL CCSD, 2007.
-
Abstract
- International audience; Thin-Plate Spline warps have been shown to be very effective as a parameterized model of the optic flow field between images of various deforming surfaces. Examples include a sheet of paper being manually handled. Recent work has used such warps for images of smooth rigid surfaces. Standard Thin-Plate Spline warps are not rigid, in the sense that they do not satisfy the epipolar geometry constraint, and are intrinsically affine, in the sense of the affine camera model. We propose three types of warps based on the Thin-Plate Spline. The first one is a flexible rigid warp. It describes the optic flow field induced by a smooth rigid surface, and satisfies the affine epipolar geometry constraint. The second and third ones extend the standard Thin-Plate Spline and the proposed rigid flexible warp to the perspective camera model. The properties of these warps are studied in details, and a hierarchy is defined. Experimental results on simulated and real data are reported, showing that the proposed warps outperform the standard one in several cases of interest.
- Subjects :
- Layout
Epipolar geometry
Optical flow
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Parameterized complexity
Geometry
Image processing
02 engineering and technology
Image motion analysis
Affine geometry
Physics::Fluid Dynamics
Uninterruptible power systems
Artificial Intelligence
Perspective camera
0202 electrical engineering, electronic engineering, information engineering
Image warping
Thin plate spline
Mathematics
ComputingMethodologies_COMPUTERGRAPHICS
business.industry
Mathematical analysis
Shape
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
020207 software engineering
Spline
Cameras
Flow field
Geometrical optics
Spline (mathematics)
Computer Science::Sound
Optical sensors
Solid modeling
020201 artificial intelligence & image processing
Deformable models
Artificial intelligence
Computer Vision and Pattern Recognition
Affine transformation
business
Algorithm
Software
Subjects
Details
- Language :
- English
- ISBN :
- 978-1-4244-1179-5
1-4244-1179-3 - ISBNs :
- 9781424411795 and 1424411793
- Database :
- OpenAIRE
- Journal :
- 2007 IEEE Conference on Computer Vision and Pattern Recognition ; ISBN: 1-4244-1179-3, International Conference on Computer Vision and Pattern Recognition (CVPR 2007), International Conference on Computer Vision and Pattern Recognition (CVPR 2007), Jun 2007, Minneapolis, United States. ⟨10.1109/CVPR.2007.382998⟩, CVPR'07-Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Minneapolis, USA, International Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2007, Minneapolis, United States, CVPR
- Accession number :
- edsair.doi.dedup.....99aef17199c9bab8bfddfbbc27e85345