{"id":342,"date":"2017-12-14T23:43:59","date_gmt":"2017-12-14T23:43:59","guid":{"rendered":"http:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/?page_id=342"},"modified":"2017-12-15T20:33:43","modified_gmt":"2017-12-15T20:33:43","slug":"pedestrian-tracking","status":"publish","type":"page","link":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/pedestrian-tracking\/","title":{"rendered":"Pedestrian Tracking"},"content":{"rendered":"<h2><span style=\"font-weight: 400\">Pedestrian Tracking<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Description: the tracking module is for tracking multiple pedestrians within 20-meter range of the infrastructure. It should reliably tracks each of the existing pedestrian and handle new ones who are stepping into the range for the first time.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Current status: the module is able to track single pedestrian reliably. The module utilizes the information from prediction module and associate the nearest detected points to the predicted position. <\/span><\/p>\n<p><span style=\"font-weight: 400\">Analysis testing: the unit test for tracking module is conducted by assigning human agent to walk between coordinate (20, 0) to (20, 3) repeatedly. The detected points\u2019 y-coordinates versus time frame are stored and visualized. The optimal shape of the graph should be sine-wave like and y-coordinate value should be within the range of (-0.3, 3.3). The tracking test graph is shown below:<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone  wp-image-343\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-content\/uploads\/sites\/26\/2017\/12\/predictionplot.png\" alt=\"\" width=\"450\" height=\"347\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Pedestrian Tracking Description: the tracking module is for tracking multiple pedestrians within 20-meter range of the infrastructure. It should reliably tracks each of the existing pedestrian and handle new ones who are stepping into the range for the first time. Current status: the module is able to track single pedestrian reliably. The module utilizes the<br \/><a class=\"moretag\" href=\"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/pedestrian-tracking\/\">+ Read More<\/a><\/p>\n","protected":false},"author":115,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-342","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/pages\/342","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/users\/115"}],"replies":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/comments?post=342"}],"version-history":[{"count":3,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/pages\/342\/revisions"}],"predecessor-version":[{"id":378,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/pages\/342\/revisions\/378"}],"wp:attachment":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2017teame\/wp-json\/wp\/v2\/media?parent=342"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}