{"id":2898,"date":"2011-02-18T17:47:50","date_gmt":"2011-02-18T17:47:50","guid":{"rendered":"http:\/\/hgpu.org\/?p=2898"},"modified":"2011-02-18T17:47:50","modified_gmt":"2011-02-18T17:47:50","slug":"accelerating-image-feature-comparisons-using-cuda-on-commodity-hardware","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2898","title":{"rendered":"Accelerating Image Feature Comparisons using CUDA on Commodity Hardware"},"content":{"rendered":"<p>Given multiple images of the same scene, image registration is the process of determining the correct transformation to bring the images into a common coordinate system-i.e., how the images fit together. Featurebased registration applies a transformation function to the input images before performing the correlation step. The result of that transformation, also called feature extraction, is a list of significant points in the images, and the registration process will attempt to correlate these points, rather than directly comparing the input images.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Given multiple images of the same scene, image registration is the process of determining the correct transformation to bring the images into a common coordinate system-i.e., how the images fit together. Featurebased registration applies a transformation function to the input images before performing the correlation step. The result of that transformation, also called feature extraction, [&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":[89,33,3],"tags":[14,106,1786,365,20,436,252],"class_list":["post-2898","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-image-processing","category-paper","tag-cuda","tag-gpu-cluster","tag-image-processing","tag-image-registration","tag-nvidia","tag-nvidia-geforce-gtx-295","tag-openmp"],"views":1833,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2898","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=2898"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2898\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2898"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2898"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2898"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}