Template Assembly for Detailed Urban Reconstruction

We propose a new framework to reconstruct building details by automatically assembling 3D templates on coarse textured building models. In a preprocessing step, we generate an initial coarse model to approximate a point cloud computed using Structure from Motion and Multi View Stereo, and we model a...

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Bibliographic Details
Published in:Computer graphics forum Vol. 34; no. 2; pp. 217 - 228
Main Authors: Nan, Liangliang, Jiang, Caigui, Ghanem, Bernard, Wonka, Peter
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.05.2015
Subjects:
3-D graphics
Analysis
and systems
Assembling
Assembly
Buildings
Categories and Subject Descriptors (according to ACM CCS)
Construction
I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Geometric algorithms
I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Geometric algorithms, languages, and systems
Image processing systems
languages
Optimization
Surface layer
Texture
Three dimensional models
Urban areas
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Description
Summary:We propose a new framework to reconstruct building details by automatically assembling 3D templates on coarse textured building models. In a preprocessing step, we generate an initial coarse model to approximate a point cloud computed using Structure from Motion and Multi View Stereo, and we model a set of 3D templates of facade details. Next, we optimize the initial coarse model to enforce consistency between geometry and appearance (texture images). Then, building details are reconstructed by assembling templates on the textured faces of the coarse model. The 3D templates are automatically chosen and located by our optimization‐based template assembly algorithm that balances image matching and structural regularity. In the results, we demonstrate how our framework can enrich the details of coarse models using various data sets.
Bibliography:Supporting InformationSupporting InformationSupporting Information
ArticleID:CGF12554
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12554