{"id":69,"date":"2018-12-11T06:23:34","date_gmt":"2018-12-11T06:23:34","guid":{"rendered":"http:\/\/mscvprojects.ri.cmu.edu\/2018team3\/?page_id=69"},"modified":"2018-12-11T06:23:34","modified_gmt":"2018-12-11T06:23:34","slug":"approach-summary","status":"publish","type":"page","link":"https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/approach-summary\/","title":{"rendered":"Approach Summary"},"content":{"rendered":"<p><strong>Approach Summary:<\/strong><\/p>\n<p>Our approach has 3 stages:<\/p>\n<ul>\n<li>Image Preprocessing<\/li>\n<li>Object detection and tracking<\/li>\n<li>Vehicle pose recovery<\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-70\" src=\"http:\/\/mscvprojects.ri.cmu.edu\/2018team3\/wp-content\/uploads\/sites\/5\/2018\/12\/approach1-300x124.png\" alt=\"\" width=\"300\" height=\"124\" srcset=\"https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/wp-content\/uploads\/sites\/5\/2018\/12\/approach1-300x124.png 300w, https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/wp-content\/uploads\/sites\/5\/2018\/12\/approach1-768x317.png 768w, https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/wp-content\/uploads\/sites\/5\/2018\/12\/approach1-1024x422.png 1024w, https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/wp-content\/uploads\/sites\/5\/2018\/12\/approach1.png 1377w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>&nbsp;<\/p>\n<p>We apply the preprocessing stage to achieve the following:<\/p>\n<ul>\n<li>Obtain a stable video<\/li>\n<li>Identify interest regions by performing background subtraction and ROI proposal using contour detection and clustering<\/li>\n<li>The ROI proposal is also essential in partitioning the image such that it can be parallely processed by 4 TX2s available for object detections and vehicle keypoint detection<\/li>\n<li>Preprocessing happens on the NUC<\/li>\n<\/ul>\n<p>Once the image has been pre-processed we perform vehicle detection and tracking. We then perform vehicle keypoint detection in the tracked boxes. Vehicle pose recovery is performed using EPnP.<\/p>\n<p>The software pipeline is explained in detail on the github page<\/p>\n<p><a href=\"https:\/\/github.com\/snlakshm\/surveillance_application\">https:\/\/github.com\/snlakshm\/surveillance_application<\/a><\/p>\n<p>and the Fall final presentation:<\/p>\n<p><a href=\"https:\/\/docs.google.com\/presentation\/d\/e\/2PACX-1vTdsSooEL7Z-R1nj8G7R5dGx99uLREfPHj6wcnNFMDmxi9C5dvJmF6IawQJDNJQE05HLHQ_zJUMi5u6\/pub?start=false&amp;loop=false&amp;delayms=3000\">https:\/\/docs.google.com\/presentation\/d\/e\/2PACX-1vTdsSooEL7Z-R1nj8G7R5dGx99uLREfPHj6wcnNFMDmxi9C5dvJmF6IawQJDNJQE05HLHQ_zJUMi5u6\/pub?start=false&amp;loop=false&amp;delayms=3000<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Approach Summary: Our approach has 3 stages: Image Preprocessing Object detection and tracking Vehicle pose recovery &nbsp; We apply the preprocessing stage to achieve the following: Obtain a stable video Identify interest regions by performing background subtraction and ROI proposal using contour detection and clustering The ROI proposal is also essential in partitioning the image &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/approach-summary\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Approach Summary&#8221;<\/span><\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-69","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Approach Summary - Platform Pittsburgh<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mscvprojects.ri.cmu.edu\/2018team3\/approach-summary\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Approach Summary - Platform Pittsburgh\" \/>\n<meta property=\"og:description\" content=\"Approach Summary: Our approach has 3 stages: Image Preprocessing Object detection and tracking Vehicle pose recovery &nbsp; 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