{"id":11190,"date":"2014-01-05T23:47:02","date_gmt":"2014-01-05T21:47:02","guid":{"rendered":"http:\/\/hgpu.org\/?p=11190"},"modified":"2014-01-05T23:47:02","modified_gmt":"2014-01-05T21:47:02","slug":"large-scale-3d-shape-retrieval-by-exploiting-multi-core-and-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=11190","title":{"rendered":"Large scale 3D shape retrieval by exploiting multi-core and GPU"},"content":{"rendered":"<p>This paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large 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 deal with the first consideration, namely the computational efficiency of 3D object retrieval by exploiting new implementations based on parallel computing by exploiting multi-core and GPU architectures. Experimental results, show that the large scale retrieval can be achieved using the multi-core environment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large 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 [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,11,73,89,3],"tags":[1787,1782,1791,14,20,1494,220],"class_list":["post-11190","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-computer-vision","category-nvidia-cuda","category-paper","tag-algorithms","tag-computer-science","tag-computer-vision","tag-cuda","tag-nvidia","tag-nvidia-geforce-gt-610","tag-sift"],"views":2386,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11190","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11190"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/11190\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11190"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11190"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11190"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}