Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/82582
Citations
Scopus Web of Science® Altmetric
?
?
Type: Conference paper
Title: Robust data modelling using thin plate splines
Author: Tennakoon, R.
Bab-Hadiashar, A.
Suter, D.
Cao, Z.
Citation: 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA, Hobart, Tasmania, 26-28 Novemeber 2013: 8 p.
Publisher: IEEE
Publisher Place: United States
Issue Date: 2013
ISBN: 9781479921263
Conference Name: International Conference on Digital Image Computing: Techniques and Applications (2013 : Hobart, Tasmania)
Statement of
Responsibility: 
Ruwan B. Tennakoon, Alireza Bab-Hadiashar, David Suter and Zhenwei Cao
Abstract: Using splines to model spatio-temporal data is one of the most common methods of data fitting used in a variety of computer vision applications. Despite its ubiquitous applications, particularly for volumetric image registration and interpolation, the existing estimation methods are still sensitive to the existence of noise and outliers. A method of robust data modelling using thin plate splines, based upon the well-known least K-th order statistical model fitting, is proposed and compared with the best available robust spline fitting techniques. Our experiments show that existing methods are not suitable for typical computer vision applications where outliers are structured (pseudo-outliers) while the proposed method performs well even when there are numerous pseudo-outliers.
Rights: Copyright © 2013 by the Institute of Electrical and Electronic Engineers
RMID: 0020134968
DOI: 10.1109/DICTA.2013.6691522
Grant ID: http://purl.org/au-research/grants/arc/DP130102524
Description (link): http://www.aprs.org.au/dicta13/
Appears in Collections:Computer Science publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.