Optimizing Query Perturbations to Enhance Shape Retrieval

Bilal Mokhtari, Kamal Eddine Melkemi, Dominique Michelucci, Sebti Foufou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

3D Shape retrieval algorithms use shape descriptors to identify shapes in a database that are the most similar to a given key shape, called the query. Many shape descriptors are known but none is perfect. Therefore, the common approach in building 3D Shape retrieval tools is to combine several descriptors with some fusion rule. This article proposes an orthogonal approach. The query is improved with a Genetic Algorithm. The latter makes evolve a population of perturbed copies of the query, called clones. The best clone is the closest to its closest shapes in the database, for a given shape descriptor. Experimental results show that improving the query also improves the precision and completeness of shape retrieval output. This article shows evidence for several shape descriptors. Moreover, the method is simple and massively parallel.

Original languageEnglish (US)
Title of host publicationMathematical Aspects of Computer and Information Sciences - 8th International Conference, MACIS 2019, Revised Selected Papers
EditorsDaniel Slamanig, Elias Tsigaridas, Zafeirakis Zafeirakopoulos
PublisherSpringer
Pages422-437
Number of pages16
ISBN (Print)9783030431198
DOIs
StatePublished - 2020
Event8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019 - Gebze, Turkey
Duration: Nov 13 2019Nov 15 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11989 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019
CountryTurkey
CityGebze
Period11/13/1911/15/19

Keywords

  • 3D Shape matching and recognition
  • Cloning
  • Computer vision
  • Genetic Algorithms
  • Shape Descriptors
  • Shape Retrieval

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Mokhtari, B., Melkemi, K. E., Michelucci, D., & Foufou, S. (2020). Optimizing Query Perturbations to Enhance Shape Retrieval. In D. Slamanig, E. Tsigaridas, & Z. Zafeirakopoulos (Eds.), Mathematical Aspects of Computer and Information Sciences - 8th International Conference, MACIS 2019, Revised Selected Papers (pp. 422-437). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11989 LNCS). Springer. https://doi.org/10.1007/978-3-030-43120-4_33