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Improved Parameter-Free 3D Object Retrieval (IP3DOR) System with Hierarchical Clustering.


Affiliations
1 Department of Computer Science, UsmanuDanfodiyo University, Sokoto., Nigeria
 

In content-based 3D object retrieval, searching for a query object in an extensive database is essential. The existing retrieval algorithms adopt the naïve search algorithm in searching for queryobjects. This approach leads to a high cost of search and retrieval that needs to be addressed. In this research, we introduced an algorithm that calculates each cluster’s representative, that is, a 3D object that has the least dissimilarity on average to each object in the cluster. This is to improve the overall retrieval performance of [1]. We first compute the optimal hierarchical level of the database using a dendrogram, and then calculate the total number of clusters in the database. Afterwards, we calculate the feature descriptor of each cluster. When a user chooses a query object, our system then compares the feature descriptor of the query object with each of the cluster ’s representation and search the cluster with the smallest distance to the query, thereby improving the querysearching and improving the system. The proposed system was implemented, and the system's performance was evaluated against the benchmark datasets. This revealed that the execution time was reduced by 21% and increased Precision and Recall by 30.7% and 33.1%, respectively. In the future, it is suggested that the technique be improved by incorporating different machine learning algorithms and comparing the results.

Keywords

3D Object Retrieval, Hierarchical Clustering, Cluster Representative.
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  • Improved Parameter-Free 3D Object Retrieval (IP3DOR) System with Hierarchical Clustering.

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Authors

Abubakar Roko
Department of Computer Science, UsmanuDanfodiyo University, Sokoto., Nigeria
Aminu Lawal
Department of Computer Science, UsmanuDanfodiyo University, Sokoto., Nigeria
Aminu B. Muhammad
Department of Computer Science, UsmanuDanfodiyo University, Sokoto., Nigeria
Abdulgafar Usman
Department of Computer Science, UsmanuDanfodiyo University, Sokoto., Nigeria

Abstract


In content-based 3D object retrieval, searching for a query object in an extensive database is essential. The existing retrieval algorithms adopt the naïve search algorithm in searching for queryobjects. This approach leads to a high cost of search and retrieval that needs to be addressed. In this research, we introduced an algorithm that calculates each cluster’s representative, that is, a 3D object that has the least dissimilarity on average to each object in the cluster. This is to improve the overall retrieval performance of [1]. We first compute the optimal hierarchical level of the database using a dendrogram, and then calculate the total number of clusters in the database. Afterwards, we calculate the feature descriptor of each cluster. When a user chooses a query object, our system then compares the feature descriptor of the query object with each of the cluster ’s representation and search the cluster with the smallest distance to the query, thereby improving the querysearching and improving the system. The proposed system was implemented, and the system's performance was evaluated against the benchmark datasets. This revealed that the execution time was reduced by 21% and increased Precision and Recall by 30.7% and 33.1%, respectively. In the future, it is suggested that the technique be improved by incorporating different machine learning algorithms and comparing the results.

Keywords


3D Object Retrieval, Hierarchical Clustering, Cluster Representative.

References