Shape matching and clustering

Sungwoo Lim, Alex H.B. Duffy, Byungsuk Lee

Research output: Contribution to conferencePaper

Abstract

Generalising knowledge and matching patterns is a basic human trait in re-using past experiences. We often cluster (group) knowledge of similar attributes as a process of learning and or aid to manage the complexity and re-use of experiential knowledge [1, 2]. In conceptual design, an ill-defined shape may be recognised as more than one type. Resulting in shapes possibly being classified differently when different criteria are applied. This paper outlines the work being carried out to develop a new technique for shape clustering. It highlights the current methods for analysing shapes found in computer aided sketching systems, before a method is proposed that addresses shape clustering and pattern matching. Clustering for vague geometric models and multiple viewpoint support are explored.

Conference

Conference13th International Conference on Engineering Design (ICED 01)
Abbreviated titleICED 01
CityGlasgow
Period21/08/0123/08/01

Fingerprint

Pattern matching
Conceptual design

Keywords

  • classification
  • machine learning
  • taxonomies
  • design engineering

Cite this

Lim, S., Duffy, A. H. B., & Lee, B. (2001). Shape matching and clustering. Paper presented at 13th International Conference on Engineering Design (ICED 01), Glasgow, .
Lim, Sungwoo ; Duffy, Alex H.B. ; Lee, Byungsuk. / Shape matching and clustering. Paper presented at 13th International Conference on Engineering Design (ICED 01), Glasgow, .8 p.
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title = "Shape matching and clustering",
abstract = "Generalising knowledge and matching patterns is a basic human trait in re-using past experiences. We often cluster (group) knowledge of similar attributes as a process of learning and or aid to manage the complexity and re-use of experiential knowledge [1, 2]. In conceptual design, an ill-defined shape may be recognised as more than one type. Resulting in shapes possibly being classified differently when different criteria are applied. This paper outlines the work being carried out to develop a new technique for shape clustering. It highlights the current methods for analysing shapes found in computer aided sketching systems, before a method is proposed that addresses shape clustering and pattern matching. Clustering for vague geometric models and multiple viewpoint support are explored.",
keywords = "classification, machine learning, taxonomies, design engineering",
author = "Sungwoo Lim and Duffy, {Alex H.B.} and Byungsuk Lee",
note = "IMechE Professional Engineering Publishing, pp163-170; 13th International Conference on Engineering Design (ICED 01), ICED 01 ; Conference date: 21-08-2001 Through 23-08-2001",
year = "2001",
language = "English",

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Lim, S, Duffy, AHB & Lee, B 2001, 'Shape matching and clustering' Paper presented at 13th International Conference on Engineering Design (ICED 01), Glasgow, 21/08/01 - 23/08/01, .

Shape matching and clustering. / Lim, Sungwoo; Duffy, Alex H.B.; Lee, Byungsuk.

2001. Paper presented at 13th International Conference on Engineering Design (ICED 01), Glasgow, .

Research output: Contribution to conferencePaper

TY - CONF

T1 - Shape matching and clustering

AU - Lim, Sungwoo

AU - Duffy, Alex H.B.

AU - Lee, Byungsuk

N1 - IMechE Professional Engineering Publishing, pp163-170

PY - 2001

Y1 - 2001

N2 - Generalising knowledge and matching patterns is a basic human trait in re-using past experiences. We often cluster (group) knowledge of similar attributes as a process of learning and or aid to manage the complexity and re-use of experiential knowledge [1, 2]. In conceptual design, an ill-defined shape may be recognised as more than one type. Resulting in shapes possibly being classified differently when different criteria are applied. This paper outlines the work being carried out to develop a new technique for shape clustering. It highlights the current methods for analysing shapes found in computer aided sketching systems, before a method is proposed that addresses shape clustering and pattern matching. Clustering for vague geometric models and multiple viewpoint support are explored.

AB - Generalising knowledge and matching patterns is a basic human trait in re-using past experiences. We often cluster (group) knowledge of similar attributes as a process of learning and or aid to manage the complexity and re-use of experiential knowledge [1, 2]. In conceptual design, an ill-defined shape may be recognised as more than one type. Resulting in shapes possibly being classified differently when different criteria are applied. This paper outlines the work being carried out to develop a new technique for shape clustering. It highlights the current methods for analysing shapes found in computer aided sketching systems, before a method is proposed that addresses shape clustering and pattern matching. Clustering for vague geometric models and multiple viewpoint support are explored.

KW - classification

KW - machine learning

KW - taxonomies

KW - design engineering

M3 - Paper

ER -

Lim S, Duffy AHB, Lee B. Shape matching and clustering. 2001. Paper presented at 13th International Conference on Engineering Design (ICED 01), Glasgow, .