Data-aware 3D partitioning for generic shape retrieval

Ivan Sipiran, Benjamin Bustos, Tobias Schreck

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

In this paper, we present a new approach for generic 3D shape retrieval based on a mesh partitioning scheme. Our method combines a mesh global description and mesh partition descriptions to represent a 3D shape. The partitioning is useful because it helps us to extract additional information in a more local sense. Thus, part descriptions can mitigate the semantic gap imposed by global description methods. We propose to find spatial agglomerations of local features to generate mesh partitions. Hence, the definition of a distance function is stated as an optimization problem to find the best match between two shape representations. We show that mesh partitions are representative and therefore it helps to improve the effectiveness in retrieval tasks. We present exhaustive experimentation using the SHREC'09 Generic Shape Retrieval Benchmark.

Original languageEnglish
Pages (from-to)460-472
Number of pages13
JournalComputers and Graphics (Pergamon)
Volume37
Issue number5
DOIs
StatePublished - 2013
Externally publishedYes

Keywords

  • Mesh partitioning
  • Optimization matching
  • Shape retrieval

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