{"id":187482,"date":"2012-03-19T00:00:00","date_gmt":"2012-03-22T09:33:02","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/msr-vision-faculty-summit-machine-learning-for-visual-recognition-randomised-decision-forests-and-its-novel-applications\/"},"modified":"2016-08-22T11:25:57","modified_gmt":"2016-08-22T18:25:57","slug":"msr-vision-faculty-summit-machine-learning-for-visual-recognition-randomised-decision-forests-and-its-novel-applications","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/msr-vision-faculty-summit-machine-learning-for-visual-recognition-randomised-decision-forests-and-its-novel-applications\/","title":{"rendered":"MSR Vision Faculty Summit &#8211; Machine Learning for Visual Recognition: Randomised Decision Forests and Its Novel Applications"},"content":{"rendered":"<div class=\"asset-content\">\n<p>This talk begins with a quick overview of machine learning techniques we study for visual recognition. Challenges occur due to high-dimensional space and significant intraclass data variations, which demand good generalisation to unseen data. Among state-of-the-art techniques, we emphasise Randomised Decision Forests and tree-structured methods. Following concepts and principles, their applications are demonstrated for challenging novel problems: real-time action recognition, object phenotype recognition using 3D shape priors, and video-based object recognition, that we recently tackled at Imperial College jointly with Univ. of Cambridge.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This talk begins with a quick overview of machine learning techniques we study for visual recognition. Challenges occur due to high-dimensional space and significant intraclass data variations, which demand good generalisation to unseen data. Among state-of-the-art techniques, we emphasise Randomised Decision Forests and tree-structured methods. Following concepts and principles, their applications are demonstrated for challenging [&hellip;]<\/p>\n","protected":false},"featured_media":196715,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-187482","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/VSIThANDzOk","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/187482","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/187482\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/196715"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=187482"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=187482"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=187482"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=187482"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=187482"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=187482"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=187482"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=187482"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=187482"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=187482"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}