Polynomial Reconstruction of 3D sampled Curves Using Auxiliary Surface Data
(2014) IEEE International Conference on Robotics and Automation, 2014- Abstract
- This paper proposes a method for structural enhancement of a 3D sampled curve. The curve is assumed to be organized, but corrupted with low frequency noise. The proposed method approaches the notion of curve reconstruction in a novel way, where information about the structure in a scanned surface is used to reconstruct the curve. Principal Component Analysis is carried out on successive neighborhoods along the curve to estimate reduced dimensionality spaces, which allows polynomial reconstruction. The effectiveness of the proposed method is verified by both simulations and experiments.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4529872
- author
- Bagge Carlson, Fredrik LU ; Vuong, Ngoc Dung and Johansson, Rolf LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Polynomial reconstruction, 3D sampled curve, point cloud, smoothing
- host publication
- 2014 IEEE International Conference on Robotics and Automation (ICRA)
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE International Conference on Robotics and Automation, 2014
- conference location
- Hong-Kong, China
- conference dates
- 2014-06-02 - 2014-06-04
- external identifiers
-
- scopus:84929192110
- DOI
- 10.1109/ICRA.2014.6907502
- project
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- 2ab5fef3-6ed9-4893-8848-dfd66f4dd078 (old id 4529872)
- date added to LUP
- 2016-04-04 13:42:16
- date last changed
- 2024-06-04 15:07:19
@inproceedings{2ab5fef3-6ed9-4893-8848-dfd66f4dd078, abstract = {{This paper proposes a method for structural enhancement of a 3D sampled curve. The curve is assumed to be organized, but corrupted with low frequency noise. The proposed method approaches the notion of curve reconstruction in a novel way, where information about the structure in a scanned surface is used to reconstruct the curve. Principal Component Analysis is carried out on successive neighborhoods along the curve to estimate reduced dimensionality spaces, which allows polynomial reconstruction. The effectiveness of the proposed method is verified by both simulations and experiments.}}, author = {{Bagge Carlson, Fredrik and Vuong, Ngoc Dung and Johansson, Rolf}}, booktitle = {{2014 IEEE International Conference on Robotics and Automation (ICRA)}}, keywords = {{Polynomial reconstruction; 3D sampled curve; point cloud; smoothing}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Polynomial Reconstruction of 3D sampled Curves Using Auxiliary Surface Data}}, url = {{https://lup.lub.lu.se/search/files/35639354/4529873.pdf}}, doi = {{10.1109/ICRA.2014.6907502}}, year = {{2014}}, }