Please use this identifier to cite or link to this item: https://doi.org/10.1145/1409060.1409114
Title: Image-based façade modeling
Authors: Xiao, J.
Fang, T.
Tan, P. 
Zhao, P.
Ofek, E.
Quan, L.
Keywords: Building modeling
City modeling
Façade modeling
Image-based modeling
Photography
Issue Date: 1-Dec-2008
Source: Xiao, J., Fang, T., Tan, P., Zhao, P., Ofek, E., Quan, L. (2008-12-01). Image-based façade modeling. ACM Transactions on Graphics 27 (5) : -. ScholarBank@NUS Repository. https://doi.org/10.1145/1409060.1409114
Abstract: We propose in this paper a semi-automatic image-based approach to façade modeling that uses images captured along streets and relies on structure from motion to recover camera positions and point clouds automatically as the initial stage for modeling. We start by considering a building façade as a flat rectangular plane or a developable surface with an associated texture image composited from the multiple visible images. A façade is then decomposed and structured into a Directed Acyclic Graph of rectilinear elementary patches. The decomposition is carried out top-down by a recursive subdivision, and followed by a bottom-up merging with the detection of the architectural bilateral symmetry and repetitive patterns. Each subdivided patch of the flat façade is augmented with a depth optimized using the 3D points cloud. Our system also allows for an easy user feedback in the 2D image space for the proposed decomposition and augmentation. Finally, our approach is demonstrated on a large number of façades from a variety of street-side images. © 2008 ACM.
Source Title: ACM Transactions on Graphics
URI: http://scholarbank.nus.edu.sg/handle/10635/56252
ISSN: 07300301
DOI: 10.1145/1409060.1409114
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

80
checked on Dec 7, 2017

WEB OF SCIENCETM
Citations

42
checked on Nov 23, 2017

Page view(s)

28
checked on Dec 11, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.