{"id":436,"date":"2016-11-18T00:29:28","date_gmt":"2016-11-18T04:29:28","guid":{"rendered":"http:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/?page_id=436"},"modified":"2017-05-11T15:07:49","modified_gmt":"2017-05-11T19:07:49","slug":"geometry-calibration","status":"publish","type":"page","link":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/geometry-calibration\/","title":{"rendered":"Geometry Calibration"},"content":{"rendered":"<p><span style=\"font-weight: 400\">In the geometric calibration, we use the three cameras and one ABB robot arm setup to conduct our experiments(Fig 7.). We would use the images that captured by the camera-robot system to conduct the geometric calibration. We wanted to test two things, one is we could get the high-quality images from path planning part, and the other is our algorithm could deal with these image in an efficient method and provide the good accuracy. <\/span><\/p>\n<p style=\"text-align: center\">\n<p style=\"text-align: center\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-808 size-medium aligncenter\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup-246x300.png\" alt=\"\" width=\"246\" height=\"300\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup-246x300.png 246w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup-520x634.png 520w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup-360x439.png 360w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup-250x305.png 250w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup-100x122.png 100w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/camera_setup.png 664w\" sizes=\"auto, (max-width: 246px) 100vw, 246px\" \/><strong>Camera and robot arm setup<\/strong><\/p>\n<p><b>\u00a0performance evaluation<\/b><\/p>\n<p><span style=\"font-weight: 400\">After the image acquisition, we got 80 raw images per camera to conduct the camera calibration. The process time of the camera calibration was quite efficient and the RMSE reprojection error was 0.1698 pixel(Fig 7.) which was meet our SVE requirement that the reprojection error should less than 0.2 pixels<img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-807\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result.png\" alt=\"\" width=\"1477\" height=\"397\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result.png 1477w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-300x81.png 300w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-768x206.png 768w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-1024x275.png 1024w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-700x188.png 700w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-520x140.png 520w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-360x97.png 360w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-250x67.png 250w, https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-content\/uploads\/sites\/18\/2017\/05\/geometric-result-100x27.png 100w\" sizes=\"auto, (max-width: 1477px) 100vw, 1477px\" \/><\/span><\/p>\n<p style=\"text-align: center\"><strong>\u00a0Geometric calibration result( left: reconstruction result; right: reprojection error)<\/strong><\/p>\n<p><span style=\"font-weight: 400\">We also compare the denoised image and raw images in the geometric calibration. The result was quite similar, so in the geometric calibration, we could directly use the raw image and saved time doing denoising.<br \/>\n<\/span><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the geometric calibration, we use the three cameras and one ABB robot arm setup to conduct our experiments(Fig 7.). We would use the images that captured by the camera-robot system to conduct the geometric calibration. We wanted to test [&hellip;]<\/p>\n","protected":false},"author":89,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-436","page","type-page","status-publish","hentry","clearfix"],"_links":{"self":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/pages\/436","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/users\/89"}],"replies":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/comments?post=436"}],"version-history":[{"count":15,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/pages\/436\/revisions"}],"predecessor-version":[{"id":809,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/pages\/436\/revisions\/809"}],"wp:attachment":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2016teamg\/wp-json\/wp\/v2\/media?parent=436"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}