TY  - CONF
AU  - Mohammad Rouhani
AU  - Angel Sappa
A2  - CVPR
PY  - 2010//
TI  - Relaxing the 3L Algorithm for an Accurate Implicit Polynomial Fitting
BT  - 23rd IEEE Conference on Computer Vision and Pattern Recognition
SP  - 3066
EP  - 3072
N2  - This paper presents a novel method to increase the accuracy of linear fitting of implicit polynomials. The proposed method is based on the 3L algorithm philosophy. The novelty lies on the relaxation of the additional constraints, already imposed by the 3L algorithm. Hence, the accuracy of the final solution is increased due to the proper adjustment of the expected values in the aforementioned additional constraints. Although iterative, the proposed approach solves the fitting problem within a linear framework, which is independent of the threshold tuning. Experimental results, both in 2D and 3D, showing improvements in the accuracy of the fitting are presented. Comparisons with both state of the art algorithms and a geometric based one (non-linear fitting), which is used as a ground truth, are provided.
SN  - 1063-6919
SN  - 978-1-4244-6984-0
UR  - http://dx.doi.org/10.1109/CVPR.2010.5540061
N1  - ADAS
ID  - Mohammad Rouhani2010
ER  -