{"id":4775,"date":"2011-07-17T09:47:12","date_gmt":"2011-07-17T06:47:12","guid":{"rendered":"http:\/\/hgpu.org\/?p=4775"},"modified":"2011-07-17T09:47:12","modified_gmt":"2011-07-17T06:47:12","slug":"feature-based-speed-limit-sign-detection-using-a-graphics-processing-unit","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4775","title":{"rendered":"Feature-based speed limit sign detection using a graphics processing unit"},"content":{"rendered":"<p>In this study we test the idea of using a graphics processing unit (GPU) as an embedded co-processor for real-time detection of European Union (EU) speed-limit signs. The input to the system is a set of grayscale videos recorded from a forward-facing camera mounted in a vehicle. We introduce a new technique for implementing the radial symmetry detector (RSD) efficiently using the native rendering capabilities of a GPU. The technique maps the algorithms to the hardware such that the detection of speed-limit sign candidates is significantly accelerated. The system reaches up to 88% detection rate and runs at 33 frames per second on video sequences with VGA (640&#215;480) resolution on an embedded system with an Intel Atom 230 @ 1.67 GHz CPU and a NVIDIA GeForce 9400M GS GPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this study we test the idea of using a graphics processing unit (GPU) as an embedded co-processor for real-time detection of European Union (EU) speed-limit signs. The input to the system is a set of grayscale videos recorded from a forward-facing camera mounted in a vehicle. We introduce a new technique for implementing 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":[11,73,89,3],"tags":[1782,1791,14,901,20,1147,182,144],"class_list":["post-4775","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-computer-vision","category-nvidia-cuda","category-paper","tag-computer-science","tag-computer-vision","tag-cuda","tag-image-recognition","tag-nvidia","tag-nvidia-geforce-9400-m-gs","tag-opengl","tag-rendering"],"views":2317,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4775","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=4775"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4775\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4775"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4775"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4775"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}