Analysis and Exploration of Large 3D Shape Databases

Xingyu Chen

Research output: ThesisThesis fully internal (DIV)

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Exploring, examining, and manipulating 3D shapes is an increasingly important application area. In this work, we present new methods and techniques that address these tasks, as follows. For exploration, we use deep learning to create visual representations of large shape repositories. For examination and manipulation, we simplify the shapes to their essence, using so-called skeletons. Our work can serve both specialists and end users interested in navigating large collections of 3D shapes in a simple and intuitive way.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Groningen
  • Telea, Alexandru, Supervisor
  • Kosinka, Jiri, Supervisor
Award date14-Jun-2021
Place of Publication[Groningen]
Publication statusPublished - 2021

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