{"id":8210,"date":"2012-09-15T23:07:51","date_gmt":"2012-09-15T20:07:51","guid":{"rendered":"http:\/\/hgpu.org\/?p=8210"},"modified":"2012-09-15T23:07:51","modified_gmt":"2012-09-15T20:07:51","slug":"real-time-kd-tree-based-importance-sampling-of-environment-maps","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8210","title":{"rendered":"Real-time Kd-tree Based Importance Sampling of Environment Maps"},"content":{"rendered":"<p>We present a new real-time importance sampling algorithm for environment maps. Our method is based on representing environment maps using kd-tree structures, and generating samples with a single data lookup. An efficient algorithm has been developed for realtime image-based lighting applications. In this paper, we compared our algorithm with Inversion method [Fishman 1996]. We show that our proposed algorithm provides compactness and speedup as compared to Inversion method. Based on a number of rendered images, we have demonstrated that in a fixed time frame the proposed algorithm produces images with a lower noise than that of the Inversion method. We also demonstrate that our algorithm can successfully represent a wide range of material types.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present a new real-time importance sampling algorithm for environment maps. Our method is based on representing environment maps using kd-tree structures, and generating samples with a single data lookup. An efficient algorithm has been developed for realtime image-based lighting applications. In this paper, we compared our algorithm with Inversion method [Fishman 1996]. We show [&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":[180,36,11,89,3],"tags":[1797,1787,1782,14,412,413,20,379],"class_list":["post-8210","post","type-post","status-publish","format-standard","hentry","category-3d-graphics-and-realism","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-3d-graphics-and-realism","tag-algorithms","tag-computer-science","tag-cuda","tag-kd-tree","tag-monte-carlo-integration","tag-nvidia","tag-nvidia-geforce-gtx-480"],"views":2872,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8210","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=8210"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8210\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8210"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8210"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8210"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}