{"id":62,"date":"2016-02-17T21:34:07","date_gmt":"2016-02-17T20:34:07","guid":{"rendered":"http:\/\/www.pips.vision\/?page_id=62"},"modified":"2018-05-24T11:09:52","modified_gmt":"2018-05-24T09:09:52","slug":"pill-recognition","status":"publish","type":"page","link":"https:\/\/www.pips.vision\/?page_id=62","title":{"rendered":"Pill Recognition"},"content":{"rendered":"<p>Computer-Vision based Pharmaceutical Pill Recognition On Mobile Phones<\/p>\n<ul>\n<li>Robustness: Segmentation regardless of pill color using a credit-card-sized target<\/li>\n<li>Feature Estimation: Dimensions, shape, color (others on demand)<\/li>\n<li>Extensibility: Trainable to work with different objects<\/li>\n<\/ul>\n<p><iframe loading=\"lazy\" src=\"https:\/\/www.youtube-nocookie.com\/embed\/mQsOD_v2HQ8?rel=0\" width=\"854\" height=\"480\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p><strong>Note:<\/strong> The original project was designed at the end of my Master&#8217;s and the computer vision core was subsequently re-implemented along with custom tracking. Platforms: Windows, Linux, (OS X, <strong>iOS<\/strong>, <strong>Android<\/strong>, <strong>Unity<\/strong> plugin).<\/p>\n<p><strong>Publications:<\/strong><\/p>\n<ul>\n<li><u>A. Hartl<\/u> and C. Arth. <em>&#8220;Computer-Vision based Pharmaceutical Pill Recognition on Mobile Phones&#8221;<\/em>, Web proceedings of the Central European Seminar on Computer Graphics for Students (CESCG), 2010<strong><br \/>\n<\/strong><\/li>\n<li><u>A. Hartl<\/u>, C. Arth and D. Schmalstieg. <em>\u201cInstant Segmentation and Feature Extraction for Recognition of Simple Objects on Mobile Phones\u201d<\/em>, Proceedings of the Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2010<\/li>\n<li><u>A. Hartl<\/u>, C. Arth and D. Schmalstieg. <em>\u201cInstant Medical Pill Recognition on Mobile Phones\u201d<\/em>, Proceedings of the IASTED International Conference on Computer Vision, 2011<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Computer-Vision based Pharmaceutical Pill Recognition On Mobile Phones Robustness: Segmentation regardless of pill color using a credit-card-sized target Feature Estimation: Dimensions, shape, color (others on demand) Extensibility: Trainable to work with different objects Note: The original project was designed at the end of my Master&#8217;s and the computer vision core was subsequently re-implemented along with [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.pips.vision\/index.php?rest_route=\/wp\/v2\/pages\/62"}],"collection":[{"href":"https:\/\/www.pips.vision\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.pips.vision\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.pips.vision\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pips.vision\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=62"}],"version-history":[{"count":23,"href":"https:\/\/www.pips.vision\/index.php?rest_route=\/wp\/v2\/pages\/62\/revisions"}],"predecessor-version":[{"id":466,"href":"https:\/\/www.pips.vision\/index.php?rest_route=\/wp\/v2\/pages\/62\/revisions\/466"}],"wp:attachment":[{"href":"https:\/\/www.pips.vision\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=62"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}