Title :
GPU-Based for accelerating the BF-SIFT method for large scale 3D shape retrieval
Author :
Dadi, El Wardani ; Daoudi, El Mostafa
Author_Institution :
LaRi Lab., Univ. of Mohammed First, Oujda, Morocco
Abstract :
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.
Keywords :
graphics processing units; image retrieval; stereo image processing; 3D object retrieval; 3D objects; BF-SIFT method; GPU; computational efficiency; large scale 3D shape retrieval; large scale retrieval; shape matching; Feature extraction; Graphics processing units; Indexing; Shape; Three-dimensional displays; Vectors; 3D Content-based Shape Retrieval; BF-SIFT method; GPU; Large Scale Retrieval;
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2014 International Conference on
Conference_Location :
Marrakech
Print_ISBN :
978-1-4799-3823-0
DOI :
10.1109/ICMCS.2014.6911201