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							<a href="https://harvest4d.org/?p=1816" class="rp-date">October 24, 2017</a>
							<h3 class="rp-title"><a href="https://harvest4d.org/?p=1816">Proceedings SIGGRAPH Asia 2017: Visibility-Consistent Thin Surface Reconstruction Using Multi-Scale Kernels</a></h3>
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															<a href="https://harvest4d.org/?p=1816" class="rp-thumb"><img width="788" height="421" src="https://harvest4d.org/wp-content/uploads/SIGGraph-2017.jpg" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="" decoding="async" loading="lazy" srcset="https://harvest4d.org/wp-content/uploads/SIGGraph-2017.jpg 788w, https://harvest4d.org/wp-content/uploads/SIGGraph-2017-300x160.jpg 300w, https://harvest4d.org/wp-content/uploads/SIGGraph-2017-768x410.jpg 768w" sizes="(max-width: 788px) 100vw, 788px" /></a>
														<p>Visibility-Consistent Thin Surface Reconstruction Using Multi-Scale Kernels Samir Aroudj, Patrick Seemann, Fabian Langguth, Stefan Guthe and Michael Goesele, TU Darmstadt, Germany &#8211; ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia), Vol. 36, No. 6, pp. 187:1-187:13, 2017 One of the key properties of many surface reconstruction &hellip; </p>
<p><a href="https://harvest4d.org/?p=1816" class="more-link"><span class="morelink-icon">Read more</span></a></p>
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							<a href="https://harvest4d.org/?p=1666" class="rp-date">July 5, 2016</a>
							<h3 class="rp-title"><a href="https://harvest4d.org/?p=1666">XXIII ISPRS Congress 2016 &#8211; Tutorial presentation</a></h3>
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															<a href="https://harvest4d.org/?p=1666" class="rp-thumb"><img width="860" height="563" src="https://harvest4d.org/wp-content/uploads/UBO-weinmann2013-teaser1.png" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="" decoding="async" loading="lazy" srcset="https://harvest4d.org/wp-content/uploads/UBO-weinmann2013-teaser1.png 860w, https://harvest4d.org/wp-content/uploads/UBO-weinmann2013-teaser1-300x196.png 300w" sizes="(max-width: 860px) 100vw, 860px" /></a>
														{"id":120,"date":"2014-01-12T09:49:03","date_gmt":"2014-01-12T09:49:03","guid":{"rendered":"https:\/\/harvest4d.org\/?page_id=120"},"modified":"2015-04-13T23:16:10","modified_gmt":"2015-04-13T23:16:10","slug":"news","status":"publish","type":"page","link":"https:\/\/harvest4d.org\/","title":{"rendered":"News"},"content":{"rendered":"<p>The current acquisition pipeline for visual models of 3D worlds is based on a paradigm of planning a goal-oriented acquisition \u2013 sampling on site \u2013 processing. The digital model of an artifact (an object, a building, up to an entire city) is produced by planning a specific scanning campaign, carefully selecting the (often costly) acquisition devices, performing the on-site acquisition at the required resolution and then post-processing the acquired data to produce a beautified triangulated and textured model. However, in the future we will be faced with the ubiquitous availability of sensing devices that deliver different data streams that need to be processed and displayed in a new way, for example smartphones, commodity stereo cameras, cheap aerial data acquisition devices, etc.\u00a0\u00a0 <span style=\"text-decoration: underline;\"><a title=\"Project\" href=\"https:\/\/harvest4d.org\/?page_id=112\">more<\/a><\/span><\/p>\n<div id='News' class='widgets_on_page wop_tiny1  wop_small1  wop_medium1  wop_large1  wop_wide1'>\n\t\t\t<ul><p>&#8220;Geometry and Reflectance Acquisition&#8221; &#8211; Michael Weinmann, University of Bonn &#8211; Tutorial 7 at XXIII ISPRS Congress, 11 July 2016, Prague, Czech Republic Acquisition and Automatic Characterization of Scenes &#8211; From Point Clouds to Features and Objects Organizers: Martin Weinmann, Michael Weinmann, Franz Rottensteiner, Boris Jutzi &hellip; <\/p>\n<p><a href=\"https:\/\/harvest4d.org\/?p=1666\" class=\"more-link\"><span class=\"morelink-icon\">Read more<\/span><\/a><\/p>\n\t\t\t\t\t\t<\/div><!-- end .rp-summary -->\n\t\t\t\t\t\t<div class=\"rp-meta\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div><!-- end .rp-meta -->\n\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/ul><!-- end .dorayaki-rp -->\n\t   <\/li><\/ul><\/div><!-- widgets_on_page -->\n","protected":false},"excerpt":{"rendered":"<p>The current acquisition pipeline for visual models of 3D worlds is based on a paradigm of planning a goal-oriented acquisition \u2013 sampling on site \u2013 processing. The digital model of an artifact (an object, a building, up to an entire city) is produced by planning a &hellip; <\/p>\n<p><a href=\"https:\/\/harvest4d.org\/\" class=\"more-link\"><span class=\"morelink-icon\">Read more<\/span><\/a><\/p>\n","protected":false},"author":9,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"page-templates\/full-width.php","meta":{"ngg_post_thumbnail":0},"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/harvest4d.org\/index.php?rest_route=\/wp\/v2\/pages\/120"}],"collection":[{"href":"https:\/\/harvest4d.org\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/harvest4d.org\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/harvest4d.org\/index.php?rest_route=\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/harvest4d.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=120"}],"version-history":[{"count":17,"href":"https:\/\/harvest4d.org\/index.php?rest_route=\/wp\/v2\/pages\/120\/revisions"}],"predecessor-version":[{"id":851,"href":"https:\/\/harvest4d.org\/index.php?rest_route=\/wp\/v2\/pages\/120\/revisions\/851"}],"wp:attachment":[{"href":"https:\/\/harvest4d.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=120"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}