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Mokhtari Bilal, Melkemi Kamal E., Michelucci Dominique, Foufou Sebti: Optimizing Query Perturbations to Enhance Shape Retrieval

Citation:

Mokhtari Bilal, Melkemi Kamal E., Michelucci Dominique, Foufou Sebti: Optimizing Query Perturbations to Enhance Shape Retrieval. In: Mathematical Aspects of Computer and Information Sciences. Vol. LNCS 11989. Springer ; 2020. pp. 422-437.

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.

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