Observatorio de I+D+i UPM

Memorias de investigación
Ponencias en congresos:
Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework
Año:2014
Áreas de investigación
  • Tecnología electrónica y de las comunicaciones
Datos
Descripción
Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to charac- terize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.
Internacional
Si
Nombre congreso
IEEE 3DTV Conf., 3DTV-CON 2014
Tipo de participación
960
Lugar del congreso
Budapest, Hungary
Revisores
Si
ISBN o ISSN
2161-203X
DOI
10.1109/3DTV.2014.6874736
Fecha inicio congreso
02/07/2014
Fecha fin congreso
04/07/2014
Desde la página
1
Hasta la página
4
Título de las actas
Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Jose Luis Herrera Conejero (UPM)
  • Autor: Carlos Roberto del Blanco Adan (UPM)
  • Autor: Narciso Garcia Santos (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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