{"id":8356,"date":"2012-10-13T11:50:59","date_gmt":"2012-10-13T08:50:59","guid":{"rendered":"http:\/\/hgpu.org\/?p=8356"},"modified":"2012-10-13T11:50:59","modified_gmt":"2012-10-13T08:50:59","slug":"mean-shift-for-graph-bundling","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8356","title":{"rendered":"Mean shift for graph bundling"},"content":{"rendered":"<p>We present a fast and simple adaption of the well-known mean shift technique for image segmentation to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply the equivalent of mean shift segmentation on this image, i.e. sharpen the image my moving the drawn edges upstream in the density&#8217;s gradient. We implement our method using standard graphics acceleration techniques. Our results are similar to state-of-the-art graph bundling methods but require a fraction of their cost. We demonstrate our method on several large graphs.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present a fast and simple adaption of the well-known mean shift technique for image segmentation to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply the equivalent of mean shift segmentation on this image, i.e. sharpen the [&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":[1782,158,20,183,974,182],"class_list":["post-8356","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-paper","tag-computer-science","tag-graph-theory","tag-nvidia","tag-nvidia-geforce-8800-gtx","tag-nvidia-geforce-gtx-580","tag-opengl"],"views":2352,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8356","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=8356"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8356\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8356"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8356"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8356"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}