{"id":4180,"date":"2011-05-30T19:56:35","date_gmt":"2011-05-30T19:56:35","guid":{"rendered":"http:\/\/hgpu.org\/?p=4180"},"modified":"2011-05-30T19:56:35","modified_gmt":"2011-05-30T19:56:35","slug":"gpu-accelerated-background-generation-algorithm-with-low-latency","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4180","title":{"rendered":"GPU-Accelerated Background Generation Algorithm with Low Latency"},"content":{"rendered":"<p>A background model is constructed to detect moving objects in video sequences. Subsequent frames are stacked on top of each other using associated registration information that must be obtained in a preprocessing step. The change of the brightness value in each pixel over time might be caused by a moving object. Current graphics processing units (GPUs) have proven to be very capable parallel processing architectures which can outperform current CPUs by an order of a magnitude. This paper will present how current GPUs can be used to rapidly construct background models from a sequence of video still frames. We will specifically discuss how the implementation can benefit from special features of GPUs that are available in the graphics API OpenGL.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A background model is constructed to detect moving objects in video sequences. Subsequent frames are stacked on top of each other using associated registration information that must be obtained in a preprocessing step. The change of the brightness value in each pixel over time might be caused by a moving object. Current graphics processing units [&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":[36,33,3],"tags":[1787,1786,365,182],"class_list":["post-4180","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-image-processing","category-paper","tag-algorithms","tag-image-processing","tag-image-registration","tag-opengl"],"views":2127,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4180","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=4180"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4180\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4180"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4180"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4180"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}