Curvature Regularization for Curves and Surfaces in a Global Optimization Framework
(2011) 8th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), 2011- Abstract
- Length and area regularization are commonplace for inverse problems today. It has however turned out to be much more difficult to incorporate a curvature prior. In this paper we propose several improvements to a recently proposed framework based on global optimization. We identify and solve an issue with extraneous arcs in the original formulation by introducing region consistency constraints. The mesh geometry is analyzed both from a theoretical and experimental viewpoint and hexagonal meshes are shown to be superior. We demonstrate that adaptively generated meshes significantly improve the performance. Our final contribution is that we generalize the framework to handle mean curvature regularization for 3D surface completion and... (More)
- Length and area regularization are commonplace for inverse problems today. It has however turned out to be much more difficult to incorporate a curvature prior. In this paper we propose several improvements to a recently proposed framework based on global optimization. We identify and solve an issue with extraneous arcs in the original formulation by introducing region consistency constraints. The mesh geometry is analyzed both from a theoretical and experimental viewpoint and hexagonal meshes are shown to be superior. We demonstrate that adaptively generated meshes significantly improve the performance. Our final contribution is that we generalize the framework to handle mean curvature regularization for 3D surface completion and segmentation. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1966791
- author
- Strandmark, Petter LU and Kahl, Fredrik LU
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- in press
- subject
- host publication
- Lecture Notes in Computer Science
- publisher
- Springer
- conference name
- 8th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), 2011
- conference location
- Saint Petersburg, Russian Federation
- conference dates
- 2011-07-25 - 2011-07-27
- language
- English
- LU publication?
- yes
- id
- 9c45a964-63eb-4731-aa6f-9562523a9e17 (old id 1966791)
- alternative location
- http://www.maths.lth.se/vision/publdb/reports/pdf/strandmark-kahl-e-11.pdf
- date added to LUP
- 2016-04-04 10:40:10
- date last changed
- 2019-04-30 17:05:47
@inproceedings{9c45a964-63eb-4731-aa6f-9562523a9e17, abstract = {{Length and area regularization are commonplace for inverse problems today. It has however turned out to be much more difficult to incorporate a curvature prior. In this paper we propose several improvements to a recently proposed framework based on global optimization. We identify and solve an issue with extraneous arcs in the original formulation by introducing region consistency constraints. The mesh geometry is analyzed both from a theoretical and experimental viewpoint and hexagonal meshes are shown to be superior. We demonstrate that adaptively generated meshes significantly improve the performance. Our final contribution is that we generalize the framework to handle mean curvature regularization for 3D surface completion and segmentation.}}, author = {{Strandmark, Petter and Kahl, Fredrik}}, booktitle = {{Lecture Notes in Computer Science}}, language = {{eng}}, publisher = {{Springer}}, title = {{Curvature Regularization for Curves and Surfaces in a Global Optimization Framework}}, url = {{https://lup.lub.lu.se/search/files/5593380/1966792.pdf}}, year = {{2011}}, }