Non-linear optimization for robust estimation of vanishing points

Nieto Doncel, Marcos y Salgado Álvarez de Sotomayor, Luis (2010). Non-linear optimization for robust estimation of vanishing points. En: "17th International Conference on Image Processing, ICIP 2010", 26/09/2010 - 29/09/2010, Hong Kong, China. ISBN 978-1-4244-7992-4.

Descripción

Título: Non-linear optimization for robust estimation of vanishing points
Autor/es:
  • Nieto Doncel, Marcos
  • Salgado Álvarez de Sotomayor, Luis
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 17th International Conference on Image Processing, ICIP 2010
Fechas del Evento: 26/09/2010 - 29/09/2010
Lugar del Evento: Hong Kong, China
Título del Libro: Proceedings of IEEE 17th International Conference on Image Processing, ICIP 2010
Fecha: Diciembre 2010
ISBN: 978-1-4244-7992-4
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (708kB) | Vista Previa

Resumen

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.

Más información

ID de Registro: 9256
Identificador DC: http://oa.upm.es/9256/
Identificador OAI: oai:oa.upm.es:9256
URL Oficial: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5652381&tag=1
Depositado por: Memoria Investigacion
Depositado el: 14 Oct 2011 07:47
Ultima Modificación: 20 Abr 2016 17:45
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM