Title
Identification and Modelling of Translational and Axial Symmetries and their Hierarchical Structures in Building Footprints by Formal Grammars.
Abstract
Buildings and other man-made objects, for many reasons such as economical or aesthetic, are often characterized by their symmetry. The latter predominates in the design of building footprints and building parts such as facades. Thus the identification and modeling of this valuable information facilitates the reconstruction of these buildings and their parts. This article presents a novel approach for the automatic identification and modelling of symmetries and their hierarchical structures in building footprints, providing an important prior for facade and roof reconstruction. The uncertainty of symmetries is explicitly addressed using supervised machine learning methods, in particular Support Vector Machines (SVMs). Unlike classical statistical methods, for SVMs assumptions on the a priori distribution of the data are not required. Both axial and translational symmetries are detected. The quality of the identified major and minor symmetry axes is assessed by a least squares based adjustment. Context-free formal grammar rules are used to model the hierarchical and repetitive structure of the underlying footprints. We present an algorithm which derives grammar rules based on the previously acquired symmetry information and using lexical analysis describing regular patterns and palindrome-like structures. This offers insights into the latent structures of building footprints and therefore describes the associated facade in a relational and compact way.
Year
DOI
Venue
2016
10.1111/tgis.12177
TRANSACTIONS IN GIS
Field
DocType
Volume
Rule-based machine translation,Data mining,Computer science,Theoretical computer science,Artificial intelligence,Machine learning,Homogeneous space
Journal
20.0
Issue
ISSN
Citations 
5.0
1361-1682
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Youness Dehbi151.93
Gerhard Gröger2558.41
Lutz Plümer314123.12