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Shape Compaction

  • Honghua LiEmail author
  • Hao Zhang
Conference paper
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

We cover and discuss techniques that are designed for compaction of shape representations or shape configurations. The goal of compaction is to reduce storage space, a fundamental problem in many application domains. We consider compaction both at the representation level (i.e., digital storage) and in physical domains (i.e., physical storage). Shape representation compaction focuses on reducing the memory space allocated for storing the shape geometry data, whilst shape compaction techniques in the physical domain reduce the physical space occupied by shape configuration. We use the term shape configuration to refer to how a shape, real or conceptual, is physically modeled (e.g., design and composition of its parts) and spatially arranged (e.g., shape parts positioning and possibly in relation to other shapes). In this paper we briefly cover the representation compaction techniques whilst placing our focus on the less explored realm of shape compaction approaches on physical configurations.

Keywords

Shape Representation Input Shape Curve Skeleton Statistical Redundancy Shape Compaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Simon Fraser UniversityBurnabyCanada

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