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Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

Torna all'elenco Report e working Paper anno 2019

Report e working Paper

Tipo: Rapporto tecnico

Titolo: A Survey on 3D Shape Segmentation with Focus on Digital Fabrication

Anno di pubblicazione: 2019

Formato: Elettronico

Autori: Filoscia I.; Alderighi T., Cignoni P.; Giorgi D.; Malomo L.

Affiliazioni autori: University of Pisa, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

Autori CNR:

  • THOMAS ALDERIGHI
  • PAOLO CIGNONI
  • DANIELA GIORGI
  • LUIGI MALOMO

Lingua: inglese

Sintesi: Segmenting 3D objects into parts is fundamental to a number of applications in computer graphics, including parametrization, texture mapping, shape matching, morphing, multi-resolution modeling, mesh editing, compression and animation [22]. Broadly speaking, shape segmentation techniques can be divided into geometry-based and semantics-based techniques. Geometry-based segmentations aim to partition the object into parts which have well-defined geometric properties such as size, curvature, or distance to a fitting primitive like a plane. Semantics-based segmentations, in turn, aim at identifying parts which are either visually relevant or meaningful in a given context, such as functional parts on mechanical objects or body parts on human models. Recently, 3D segmentation also drawn attention as a tool for efficient fabrication. The decomposition of objects into parts, indeed, helps solving different issues related to fabrication, such as height field constraints, volume constraints and need for supporting structures. In this work we present a complete survey of segmentation techniques, also highlighting their strengths and weaknesses. Our aim is to produce a handy overview to people who want to approach the problem of segmentation, especially if they want to apply it to digital fabrication.

Lingua sintesi: eng

Parole chiave:

  • 3D shape analysis
  • 3D model segmentation
  • computational fabrication

Strutture CNR:

 
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