{"id":2325,"date":"2011-01-05T21:03:54","date_gmt":"2011-01-05T21:03:54","guid":{"rendered":"http:\/\/hgpu.org\/?p=2325"},"modified":"2011-01-05T21:03:54","modified_gmt":"2011-01-05T21:03:54","slug":"cullide-interactive-collision-detection-between-complex-models-in-large-environments-using-graphics-hardware","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2325","title":{"rendered":"CULLIDE: interactive collision detection between complex models in large environments using graphics hardware"},"content":{"rendered":"<p>We present a novel approach for fast collision detection between multiple deformable and breakable objects in a large environment using graphics hardware. Our algorithm takes into account low bandwidth to and from the graphics cards and computes a potentially colliding set (PCS) using visibility queries. It involves no precomputation and proceeds in multiple stages: PCS computation at an object level and PCS computation at sub-object level, followed by exact collision detection. We use a linear time two-pass rendering algorithm to compute each PCS efficiently. The overall approach makes no assumption about the input primitives or the object&#8217;s motion and is directly applicable to all triangulated models. It has been implemented on a PC with NVIDIA GeForce FX 5800 Ultra graphics card and applied to different environments composed of a high number of moving objects with tens of thousands of triangles. It is able to compute all the overlapping primitives between different objects up to image-space resolution in a few milliseconds.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present a novel approach for fast collision detection between multiple deformable and breakable objects in a large environment using graphics hardware. Our algorithm takes into account low bandwidth to and from the graphics cards and computes a potentially colliding set (PCS) using visibility queries. It involves no precomputation and proceeds in multiple stages: PCS [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","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":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[11,3],"tags":[137,1782,20,414,182],"class_list":["post-2325","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-collision-detection","tag-computer-science","tag-nvidia","tag-nvidia-geforce-fx-5800-ultra","tag-opengl"],"views":2059,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2325","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=2325"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2325\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2325"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2325"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2325"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}