{"id":2277,"date":"2010-12-29T12:58:11","date_gmt":"2010-12-29T12:58:11","guid":{"rendered":"http:\/\/hgpu.org\/?p=2277"},"modified":"2010-12-29T12:58:11","modified_gmt":"2010-12-29T12:58:11","slug":"high-performance-realtime-vision-for-mobile-robots-on-the-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2277","title":{"rendered":"High performance realtime vision for mobile robots on the GPU"},"content":{"rendered":"<p>We present a real time vision system designed for and implemented on a graphics processing unit (GPU). After an introduction in GPU programming we describe the architecture of the system and software running on the GPU. We show the advantages of implementing a vision processor on the GPU rather than on a CPU as well as the shortcomings of this approach. Our performance measurements show that the GPU-based vision system including colour segmentation, pattern recognition and edge detection easily meets the requirements for high resolution (1024&#215;768) colour image processing at a rate of up to 50 frames per second. A CPU-based implementation on a mobile PC would under these constraints achieve only around twelve frames per second. The source code of this system is available online [1].<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present a real time vision system designed for and implemented on a graphics processing unit (GPU). After an introduction in GPU programming we describe the architecture of the system and software running on the GPU. We show the advantages of implementing a vision processor on the GPU rather than on a CPU as well [&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":[11,73,3],"tags":[1782,1791,20,317,182,176],"class_list":["post-2277","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-computer-vision","category-paper","tag-computer-science","tag-computer-vision","tag-nvidia","tag-nvidia-geforce-6800","tag-opengl","tag-package"],"views":2501,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2277","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=2277"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2277\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2277"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2277"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2277"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}