{"id":352784,"date":"2017-01-14T17:19:39","date_gmt":"2017-01-15T01:19:39","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=352784"},"modified":"2018-10-16T20:20:00","modified_gmt":"2018-10-17T03:20:00","slug":"real-time-facial-expression-mapping-high-resolution-3d-meshes","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/real-time-facial-expression-mapping-high-resolution-3d-meshes\/","title":{"rendered":"Real-Time Facial Expression Mapping for High Resolution 3D Meshes"},"content":{"rendered":"<div id=\"kb-nav--main\" class=\"col-main has-full-enumeration\">\n<div>\n<section id=\"Abs1\" class=\"Abstract\" lang=\"en\">\n<p class=\"Para\">We present a learning-based 3D facial expression mapping technique that preserves facial expression details and works in real time for even high resolution meshes. Our approach is inspired by a previously developed technique called deformation transfer [1]. The deformation transfer technique preserves facial expression details but its computational overhead makes it not suitable for real time applications. To accelerate computation, we use a piecewise linear function to represent the mapping from the <em class=\"EmphasisTypeItalic \">direct motion<\/em> (the difference between the expression face and the neutral face) to the motion obtained by the deformation transfer method. This piecewise linear function is learned offline from a small set of training data. The online computation is thus reduced to the evaluation of the piecewise linear functions which is significantly faster. As a result, we are able to perform real time expression mapping for even high resolution 3D meshes.<\/p>\n<\/section>\n<\/div>\n<\/div>\n<div id=\"kb-nav--aside\" class=\"col-aside\"><\/div>\n","protected":false},"excerpt":{"rendered":"<p>We present a learning-based 3D facial expression mapping technique that preserves facial expression details and works in real time for even high resolution meshes. Our approach is inspired by a previously developed technique called deformation transfer [1]. The deformation transfer technique preserves facial expression details but its computational overhead makes it not suitable for real [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"Springer Berlin Heidelberg","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"24th Computer Graphics International Conference","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"24th Computer Graphics International 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