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Karia Ba Mohamed, Morocco

Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First | Tadonki C.,MINES ParisTech
Proceedings of 2012 International Conference on Complex Systems, ICCS 2012 | Year: 2012

In this work, we present a new technique to speed up 3D shape retrieval. Instead of performing an exhaustive search over the whole database, which implies a systematic comparison of the query object with all 3D objects in the database, we restrict the pattern matching to a subset of 'good candidates' (the most similar to the query). Assuming that the database has been partitioned into several classes, our retrieval algorithm focuses on the class containing objects that are similar to that of the query. Thus, the systematic pattern matching is performed within the selected class only. The key idea is to index each class by a suitable referent object that will be used to seek the right class on a search request with a given 3D object. In this paper, we describe how to choose the best representative within a class, and then couple it with a 3D retrieval method proposed in the literature. We illustrate the efficiency of our approach trough some experiments. © 2012 IEEE. Source


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Despite of the variety of approaches proposed in the literature in order to improve the execution time of the 3D shape retrieval [14,15], the challenge that still remains is to design a 3D shape retrieval method that allows the large scale retrieval and, in the same time, respects the relevance of the obtained results. In this work, we deal with the problem of the large scale of 3D shape retrieval by proposing new implementations on multi-core environment. At our knowledge, a few partial works based on HPC (High Performance Computing), have been proposed in the literature [1,2]. The proposed solutions are designed for the GPU (Graphical Processing Unit) and concern only the step of the extraction of the SIFT salient local features. In order to optimally exploit the potential of the multi-core architectures, we have studied different data distributions. Experimental results, under OpenMP environment, show that the large scale retrieval can be achieved using the multi-core environment. © 2013 Springer-Verlag. Source


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
International Conference on Multimedia Computing and Systems -Proceedings | Year: 2014

This paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large scale retrieval). While this problem is emerging and interesting as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: computational efficiency of 3D object retrieval and the quality of retrieved results. In this work we are interested by the problem of the computational efficiency where we propose to accelerate the BF-SIFT method by exploiting the potential of the GPU to reduce the computation times of the shape indexing of the query and the shape matching using the GPU. Experimental results show that the execution time is significantly reduced, this promises that the large scale retrieval can be achieved using the GPU. © 2014 IEEE. Source


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
Research Journal of Applied Sciences, Engineering and Technology | Year: 2014

This study addresses the problem of 3D shape retrieval. While this problem is interesting and emerging as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: Computational efficiency of 3D object retrieval and the quality of retrieval results. In this study we deal with the two considerations, especially the first one namely computational efficiency, by proposing a new technique to retrieve efficiently the 3D-objects in the classified databases which contains 3D objects of different categories. This technique can be coupled with any 3D retrieval method. In this study, we use the Clock Matching Bag-of-Features 3D retrieval method proposed by Lian et al. (2010) since it gives the best result comparing with several methods in particular the view based methods. Instead of systematically matching the object-query with all 3D objects of the target database, our approach restricts the pattern matching on a subset of "good candidates" (the most similar to the query). For a database classified in several classes the retrieval will be oriented to the right class that contains similar objects to the query. In this case, the matching process will be not systematically performed with all objects among the database, but only with objects of right class. Our key idea is to represent each class by one representative that will be used to orient the retrieval process to the right class. Experimental results illustrate the efficiency of our approach. © Maxwell Scientific Organization, 2014. Source


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First | Tadonki C.,MINES ParisTech
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

Recent investigations illustrate that view-based methods, with pose normalization pre-processing get better performances in retrieving rigid models than other approaches and still the most popular and practical methods in the field of 3D shape retrieval [9,10,11,12]. In this paper we present an improvement of the BF-SIFT method proposed by Ohbuchi et al [1]. This method is based on bag-of-features to integrate a set of features extracted from 2D views of the 3D objects using the SIFT (Scale Invariant Feature Transform [2]) algorithm into a histogram using vector quantization which is based on a global visual codebook. In order to improve the retrieval performances, we propose to associate to each 3D object its local visual codebook instead of a unique global codebook. The experimental results obtained on the Princeton Shape Benchmark database [3] show that the proposed method performs better than the original method. © 2012 Springer-Verlag. Source

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