3D registration is a computer vision technique of aligning multi-view range images with respect to a reference co-ordinate system. Aligning range images is an important and time-complex step in complete 3D reconstruction. In this paper, we propose a real-time 3D registration technique by employing the accelerated computing power of GPU (graphic processing unit). In the proposed technique, complete steps of a point-to-plane 3D registration technique are implemented using CUDA, an up-to-date GPU programming technique. Using a hand-held stereo-vision sensor, we apply the proposed technique to scan real objects. Registration of a pair of range images which size is 320×240 takes about 60 milliseconds in average. Results of 3D model reconstruction and processing time analysis are shown in experiments.<\/p>\n","protected":false},"excerpt":{"rendered":"
3D registration is a computer vision technique of aligning multi-view range images with respect to a reference co-ordinate system. Aligning range images is an important and time-complex step in complete 3D reconstruction. In this paper, we propose a real-time 3D registration technique by employing the accelerated computing power of GPU (graphic processing unit). In the […]<\/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":[1782,1791,14,365,20],"class_list":["post-3819","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-registration","tag-nvidia"],"views":1768,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3819","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=3819"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3819\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3819"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3819"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3819"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}