Shape matching and clustering

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

Research output: Contribution to conferencePaper

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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.
Original languageEnglish
Number of pages8
Publication statusPublished - 2001
Event13th International Conference on Engineering Design (ICED 01) - Glasgow
Duration: 21 Aug 200123 Aug 2001

Conference

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

Keywords

  • classification
  • machine learning
  • taxonomies
  • design engineering

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    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, .