Learning semantic models and grammar rules of building parts

Youness Dehbi; Jörg Schmittwilken; Lutz Plümer

Learning semantic models and grammar rules of building parts

Youness Dehbi, Jörg Schmittwilken, Lutz Plümer

Abstract

Building reconstruction and building model generation nowadays receives more and more attention. In this context models such as formal grammars play a major role in 3D geometric modelling. Up to now, models have been designed manually by experts such as architects. Hence, this paper describes an Inductive Logic Programming (ILP) based approach for learning semantic models and grammar rules of buildings and their parts. Due to their complex structure and their important role as link between the building and its outside, straight stairs are presented as an example. ILP is introduced and applied as machine learning method. The learning process is explained and the learned models and results are presented.

Original language	English
Title of host publication	Workshop on quality, scale and analysis aspects of city models
Editors	Lars Harrie
Number of pages	7
Publication status	Published - 2009
Externally published	Yes
Event	Workshop on quality, scale and analysis aspects of city models - Lund, Sweden Duration: 3 Dec 2009 → 4 Dec 2009

Publication series

Name	ISPRS Archives
Number	XXXVIII-2/W11

Workshop

Workshop	Workshop on quality, scale and analysis aspects of city models
Country/Territory	Sweden
City	Lund
Period	3/12/09 → 4/12/09

Keywords

Machine Learning
Inductive Logic Programming
Progol
Attribute Grammar
3D Model
Semantic Model

Access to Document

https://www.isprs.org/proceedings/XXXVIII/2-W11/Dehbi_Schmittwilken_Plumer.pdfLicence: CC BY

Cite this

@inproceedings{bffdf2def71345fb81f27899031d39df,

title = "Learning semantic models and grammar rules of building parts",

abstract = "Building reconstruction and building model generation nowadays receives more and more attention. In this context models such as formal grammars play a major role in 3D geometric modelling. Up to now, models have been designed manually by experts such as architects. Hence, this paper describes an Inductive Logic Programming (ILP) based approach for learning semantic models and grammar rules of buildings and their parts. Due to their complex structure and their important role as link between the building and its outside, straight stairs are presented as an example. ILP is introduced and applied as machine learning method. The learning process is explained and the learned models and results are presented. ",

keywords = "Machine Learning, Inductive Logic Programming, Progol, Attribute Grammar, 3D Model, Semantic Model",

author = "Youness Dehbi and J{\"o}rg Schmittwilken and Lutz Pl{\"u}mer",

year = "2009",

language = "English",

series = "ISPRS Archives",

number = "XXXVIII-2/W11",

editor = "Harrie, \{Lars \}",

booktitle = "Workshop on quality, scale and analysis aspects of city models",

note = "Workshop on quality, scale and analysis aspects of city models ; Conference date: 03-12-2009 Through 04-12-2009",

}

Dehbi, Y, Schmittwilken, J & Plümer, L 2009, Learning semantic models and grammar rules of building parts. in L Harrie (ed.), Workshop on quality, scale and analysis aspects of city models. ISPRS Archives, no. XXXVIII-2/W11, Workshop on quality, scale and analysis aspects of city models, Lund, Sweden, 3/12/09. <https://www.isprs.org/proceedings/XXXVIII/2-W11/Dehbi_Schmittwilken_Plumer.pdf>

Learning semantic models and grammar rules of building parts. / Dehbi, Youness; Schmittwilken, Jörg; Plümer, Lutz.
Workshop on quality, scale and analysis aspects of city models. ed. / Lars Harrie. 2009. (ISPRS Archives; No. XXXVIII-2/W11).

Research output: Chapter in Book (Inbook) /Conference Proceeding › Conference Paper › Research Article/Contribution › peer-review

TY - GEN

T1 - Learning semantic models and grammar rules of building parts

AU - Dehbi, Youness

AU - Schmittwilken, Jörg

AU - Plümer, Lutz

PY - 2009

Y1 - 2009

N2 - Building reconstruction and building model generation nowadays receives more and more attention. In this context models such as formal grammars play a major role in 3D geometric modelling. Up to now, models have been designed manually by experts such as architects. Hence, this paper describes an Inductive Logic Programming (ILP) based approach for learning semantic models and grammar rules of buildings and their parts. Due to their complex structure and their important role as link between the building and its outside, straight stairs are presented as an example. ILP is introduced and applied as machine learning method. The learning process is explained and the learned models and results are presented.

AB - Building reconstruction and building model generation nowadays receives more and more attention. In this context models such as formal grammars play a major role in 3D geometric modelling. Up to now, models have been designed manually by experts such as architects. Hence, this paper describes an Inductive Logic Programming (ILP) based approach for learning semantic models and grammar rules of buildings and their parts. Due to their complex structure and their important role as link between the building and its outside, straight stairs are presented as an example. ILP is introduced and applied as machine learning method. The learning process is explained and the learned models and results are presented.

KW - Machine Learning

KW - Inductive Logic Programming

KW - Progol

KW - Attribute Grammar

KW - 3D Model

KW - Semantic Model

M3 - Conference Paper

T3 - ISPRS Archives

BT - Workshop on quality, scale and analysis aspects of city models

A2 - Harrie, Lars

T2 - Workshop on quality, scale and analysis aspects of city models

Y2 - 3 December 2009 through 4 December 2009

ER -