{"id":4907,"date":"2011-07-27T15:37:56","date_gmt":"2011-07-27T12:37:56","guid":{"rendered":"http:\/\/hgpu.org\/?p=4907"},"modified":"2011-07-27T15:37:56","modified_gmt":"2011-07-27T12:37:56","slug":"accelerating-feature-extraction-for-patch-based-multi-view-stereo-algorithm","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4907","title":{"rendered":"Accelerating feature extraction for patch-based Multi-View Stereo algorithm"},"content":{"rendered":"<p>In this paper, we present a novel parallel implementation of HARRIS and DOG detector on GPU for feature extractions of Patch-based Multi-View Stereo (PMVS) algorithm in image sequence. With the Compute Unified Device Architecture(CUDA)-enabled GPU, the acceleration is significant and it obtains a 34 times performance boost comparing to a CPU implementation. We adopt the hardware built-in bilinear interpolation of texture to shorten the time for image resampling while doing image transformations. While lots of time can be saved by using our improved PMVS Algorithm with GPU-based feature extraction, experimental results also show that our implementation can obtain fine details for building accurate object and scene models.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, we present a novel parallel implementation of HARRIS and DOG detector on GPU for feature extractions of Patch-based Multi-View Stereo (PMVS) algorithm in image sequence. With the Compute Unified Device Architecture(CUDA)-enabled GPU, the acceleration is significant and it obtains a 34 times performance boost comparing to a CPU implementation. We adopt 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":[36,89,33,3],"tags":[1787,14,1786,20],"class_list":["post-4907","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-image-processing","category-paper","tag-algorithms","tag-cuda","tag-image-processing","tag-nvidia"],"views":2155,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4907","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=4907"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4907\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4907"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4907"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4907"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}