{"id":184510,"date":"2004-04-19T00:00:00","date_gmt":"2009-10-31T13:50:11","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/some-new-directions-in-energy-minimization-with-graph-cuts\/"},"modified":"2016-09-09T09:59:35","modified_gmt":"2016-09-09T16:59:35","slug":"some-new-directions-in-energy-minimization-with-graph-cuts","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/some-new-directions-in-energy-minimization-with-graph-cuts\/","title":{"rendered":"Some New Directions in Energy Minimization with Graph Cuts"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Algorithms based on graph cuts have had a major impact on an important class of vision problems.  In these problems, which arise in applications such as stereo, every pixel must be assigned a label from some predefined set.  There is a known cost to assign a given label to any pixel, as well as a known cost for assigning different labels to adjacent pixels.  I will describe some recent work that addresses a broader class of problems, where the labels are not specified in advance, and where the cost of assigning a given label to any pixel must be determined.  This broader class of problems arises from applications such as multi-modal imaging, stereo imaging with unknown camera gain\/bias, texture segmentation and layered motion segmentation. I will present some preliminary results that suggest that these problems can be solved by combining graph cuts with ideas from Expectation-Maximization and mutual information.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Algorithms based on graph cuts have had a major impact on an important class of vision problems. In these problems, which arise in applications such as stereo, every pixel must be assigned a label from some predefined set. There is a known cost to assign a given label to any pixel, as well as a [&hellip;]<\/p>\n","protected":false},"featured_media":195461,"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-184510","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/ui4IzfzD7D0","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/184510","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\/184510\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/195461"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=184510"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=184510"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=184510"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=184510"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=184510"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=184510"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=184510"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=184510"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=184510"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=184510"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}