Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/33970
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Type: Conference paper
Title: Combining single view recognition and multiple view stereo for architectural scenes
Author: Dick, A.
Torr, P.
Ruffle, S.
Cipolla, R.
Citation: Eighth IEEE International Conference on Computer Vision, 2001: pp. 268-274
Publisher: Department of English, Cambridge University
Publisher Place: Cambridge University
Issue Date: 2001
ISBN: 0769511430
Conference Name: IEEE International Conference on Computer Vision (8th : 2001 : Vancouver, Canada)
Statement of
Responsibility: 
Dick, A.R., Torr, P.H.S., Ruffle, S.J., Cipolla, R.
Abstract: This paper describes a structure from motion and recognition paradigm for generating 3D models from 2D sets of images. In particular we consider the domain of architectural photographs. A model based approach is adopted with the architectural model built from a “Lego kit” of parameterised parts. The approach taken is different from traditional stereo or shape from X approaches in that identification of the parameterised components (such as windows, doors, buttresses etc) from one image is combined with parallax information in order to generate the 3D model. This model based approach has two main benefits: first, it allows the inference of shape and texture where the evidence from the images is weak; and second, it recovers not only geometry and texture but also an interpretation of the model, which can be used for automatic enhancement techniques such as the application of reflective textures to windows
Description: ©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
DOI: 10.1109/ICCV.2001.937528
Published version: http://dx.doi.org/10.1109/iccv.2001.937528
Appears in Collections:Aurora harvest
Computer Science publications

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