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Memorias de investigación
Communications at congresses:
Non-linear optimization for robust estimation of vanishing points
Year:2010
Research Areas
  • Processing and signal analysis
Information
Abstract
A new method for robust estimation of vanishing points is introduced in this paper. It is based on the MSAC (M-estimator Sample and Consensus) algorithm and on the definition of a new distance function between a vanishing point and a given orientation. Apart from the robustness, our method represents a flexible and efficient solution, since it allows to work with different type of image data, and its iterative nature makes better use of the available information to obtain more accurate estimates. The key issue of the work is the proposed distance function, that makes the error to be independent from the position of an hypothesized vanishing point, which allows to work with points at the infinity. Besides, the estimation process is guided by a non-linear optimization process that enhances the accuracy of the system. The robustness of our proposal, compared with other methods in the literature is shown with a set of tests carried out for both synthetic data and real images. The results show that our approach obtain excellent levels of accuracy and that is definitely robust against the presence of large amounts of outliers, outperforming other state of the art approaches.
International
Si
Congress
IEEE International Conference on Image Processing, ICIP 2010
960
Place
Hong Kong, China
Reviewers
Si
ISBN/ISSN
1522-4880
10.1109/ICIP.2010.5652381
Start Date
26/09/2010
End Date
29/09/2010
From page
1885
To page
1888
Proc. IEEE International Conference on Image Processing, ICIP 2010
Participants
  • Autor: Marcos Nieto Doncel (UPM)
  • Autor: Luis Salgado Alvarez de Sotomayor (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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