Optimizing Query Perturbations to Enhance Shape Retrieval

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

doi:10.1007/978-3-030-43120-4_33

Optimizing Query Perturbations to Enhance Shape Retrieval

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

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Mathematical Aspects of Computer and Information Sciences - 8th International Conference, MACIS 2019, Revised Selected Papers
Editors	Daniel Slamanig, Elias Tsigaridas, Zafeirakis Zafeirakopoulos
Publisher	Springer
Pages	422-437
Number of pages	16
ISBN (Print)	9783030431198
DOIs	https://doi.org/10.1007/978-3-030-43120-4_33
State	Published - 2020
Event	8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019 - Gebze, Turkey Duration: Nov 13 2019 → Nov 15 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11989 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019
Country/Territory	Turkey
City	Gebze
Period	11/13/19 → 11/15/19

Keywords

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

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-43120-4_33

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

Optimizing Query Perturbations to Enhance Shape Retrieval. / Mokhtari, Bilal; Melkemi, Kamal Eddine; Michelucci, Dominique et al.
Mathematical Aspects of Computer and Information Sciences - 8th International Conference, MACIS 2019, Revised Selected Papers. ed. / Daniel Slamanig; Elias Tsigaridas; Zafeirakis Zafeirakopoulos. Springer, 2020. p. 422-437 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11989 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mokhtari, B, Melkemi, KE, 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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11989 LNCS, Springer, pp. 422-437, 8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019, Gebze, Turkey, 11/13/19. https://doi.org/10.1007/978-3-030-43120-4_33

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

Mokhtari, Bilal ; Melkemi, Kamal Eddine ; Michelucci, Dominique et al. / Optimizing Query Perturbations to Enhance Shape Retrieval. Mathematical Aspects of Computer and Information Sciences - 8th International Conference, MACIS 2019, Revised Selected Papers. editor / Daniel Slamanig ; Elias Tsigaridas ; Zafeirakis Zafeirakopoulos. Springer, 2020. pp. 422-437 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - 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.

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Optimizing Query Perturbations to Enhance Shape Retrieval

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