2010
DOI: 10.1068/b36010
|View full text |Cite
|
Sign up to set email alerts
|

Embedding Shapes without Predefined Parts

Abstract: For a practical computer implementation of part embedding in shapes that is also true to their continuous character and the shape grammar formalism, shapes and their boundaries are handled together in composite shape and label algebras. Temporary representations of shapes, termed ‘overcomplete graphs’, comprise boundary elements of shapes and how they are assembled, and are utilized in a two-phase algorithm that systematically searches for embedded parts. The associated implementation is developed to receive u… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2012
2012
2019
2019

Publication Types

Select...
5
3

Relationship

1
7

Authors

Journals

citations
Cited by 11 publications
(4 citation statements)
references
References 16 publications
0
4
0
Order By: Relevance
“…Although each one uses different representations for shapes and different approaches for part embeddings, they all treat shapes that contain straight lines, circular arcs, or free-form curves or all, equally such that the shape representations become invariant to constituting analytical forms. They either use some registration points as vertices to shape graphs to resolve structure and perform part matchings for graph edges (Keles et al, 2010; Grasl & Economou, 2013); use pixel-based representation and image processing algorithms (Jowers et al, 2010); use weighted representation of shapes and evolutionary optimization algorithms (Keles et al, 2012; Keles, 2015). In all these approaches, shapes are not treated as a composition of a set of pre-defined analytical forms but treated as continuous entities.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Although each one uses different representations for shapes and different approaches for part embeddings, they all treat shapes that contain straight lines, circular arcs, or free-form curves or all, equally such that the shape representations become invariant to constituting analytical forms. They either use some registration points as vertices to shape graphs to resolve structure and perform part matchings for graph edges (Keles et al, 2010; Grasl & Economou, 2013); use pixel-based representation and image processing algorithms (Jowers et al, 2010); use weighted representation of shapes and evolutionary optimization algorithms (Keles et al, 2012; Keles, 2015). In all these approaches, shapes are not treated as a composition of a set of pre-defined analytical forms but treated as continuous entities.…”
Section: Related Workmentioning
confidence: 99%
“…Keles et al (2010) represented shapes using over-complete graphs and determined part embeddings using the attributes of the graph nodes which define the geometric relations among the nodes in the spatial domain. Another graph-based solution is proposed by Grasl and Economou (2013) that supports emergent shape detection and parametric rule applications.…”
Section: Related Workmentioning
confidence: 99%
“…Generally speaking, the problem of recognition of embedded shapes represents one of the key challenges for practical shape grammar computer implementation, and this remains a current topic. Some of the more recent approaches to this problem can be seen in the works of Keles et al (2010;2012) and Jowers et al (2010). These approaches abandon the concept that shapes should be predefined as compositions of geometry such as points, lines, curves, or planes.…”
Section: Architecture Modeling In Urban Spacesmentioning
confidence: 99%
“…Heisserman (1991;1994) uses boundary graphs to guarantee well-formed solids during the execution of his boundary solid grammars. Keles et al (2010) present the overcomplete graph as a tool to search for embedded shapes. Further, Grasl (2012) presented Grappa, an implementation of the Palladian grammar (Stiny and Mitchell, 1978) based on graph grammars.…”
Section: Introductionmentioning
confidence: 99%