{"id":9271,"date":"2013-04-25T21:06:53","date_gmt":"2013-04-25T18:06:53","guid":{"rendered":"http:\/\/hgpu.org\/?p=9271"},"modified":"2013-04-25T21:21:28","modified_gmt":"2013-04-25T18:21:28","slug":"faster-upper-body-pose-estimation-and-recognition-using-cuda","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=9271","title":{"rendered":"Faster Upper Body Pose Estimation and Recognition Using CUDA"},"content":{"rendered":"<p>Image processing techniques can be very time consuming when applied linearly on the Central Processing Unit (CPU). Many applications require processing to take place in real-time. The Upper Body Pose Estimation and Recognition system developed by Achmed and Connan has shown to be 88% accurate, but operates at less than real-time on the CPU. This paper proposes an adapted version of this algorithm, which runs on the Graphics Processing Unit (GPU) to achieve real-time processing speed. The system was found to achieve a slightly improved recognition accuracy of 92.95% while achieving on average a real-time processing speed of no less than 18 Frames Per Second (FPS) and a mean speed of 33.26 FPS.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Image processing techniques can be very time consuming when applied linearly on the Central Processing Unit (CPU). Many applications require processing to take place in real-time. The Upper Body Pose Estimation and Recognition system developed by Achmed and Connan has shown to be 88% accurate, but operates at less than real-time on the CPU. This [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":[36,73,89,33,3],"tags":[1787,1791,14,1786,20,974],"class_list":["post-9271","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-vision","category-nvidia-cuda","category-image-processing","category-paper","tag-algorithms","tag-computer-vision","tag-cuda","tag-image-processing","tag-nvidia","tag-nvidia-geforce-gtx-580"],"views":2310,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9271","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=9271"}],"version-history":[{"count":1,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9271\/revisions"}],"predecessor-version":[{"id":9276,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/9271\/revisions\/9276"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9271"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9271"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9271"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}