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dc.date.accessioned 2012-08-06T13:29:43Z
dc.date.available 2012-08-06T13:29:43Z
dc.date.issued 2010
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/19149
dc.description.abstract Depth estimation from monocular images can be retrieved from the perspective distortion. One major e ect of this distortion is that a set of parallel lines in the real world converges into a single point in the image plane. The estimation of the coordinates of the vanishing point can be retrieved directly by di erent ways, like Hough Transform and First derivative approaches. Many of them work on speci c real scene characteristics and often lead to spurious vanishing points. Technology and computational advances suggest that some re nements to these simple techniques or a combination of them could lead to more con dent vanishing point detection than modelling and developing a new complicated ones. In this paper we study the behaviour of two classical approaches, introduce them some improvements and propose a new combinational technique to estimate the location of the vanishing point in an image. The solutions will be described and compared, also through the discussion of the results obtained from their application to real images. en
dc.format.extent 444-454 es
dc.language en es
dc.subject Procesamiento de Imagen Asistida por Computador es
dc.subject image analysis; computer vision; digital image processing en
dc.title Lineal perspective estimation on monocular images en
dc.type Objeto de conferencia es
sedici.identifier.isbn 978-950-9474-49-9 es
sedici.creator.person Chappero, Eugenio J. es
sedici.creator.person Guerrero, Roberto A. es
sedici.creator.person Serón Arbeloa, Francisco J. es
sedici.description.note Presentado en el VIII Workshop Computación Gráfica, Imágenes y Visualización (WCGIV) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2010-10
sedici.relation.event XVI Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)