{"id":2,"date":"2024-04-29T19:15:57","date_gmt":"2024-04-29T19:15:57","guid":{"rendered":"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/?page_id=2"},"modified":"2024-05-10T18:15:32","modified_gmt":"2024-05-10T18:15:32","slug":"introduction","status":"publish","type":"page","link":"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/introduction\/","title":{"rendered":"Introduction"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"234\" src=\"http:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/CameraArray-1024x234.png\" alt=\"\" class=\"wp-image-51\" style=\"width:665px;height:auto\" srcset=\"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/CameraArray-1024x234.png 1024w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/CameraArray-300x68.png 300w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/CameraArray-768x175.png 768w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/CameraArray-1536x350.png 1536w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/CameraArray.png 1754w\" sizes=\"auto, (max-width: 706px) 89vw, (max-width: 767px) 82vw, 740px\" \/><figcaption class=\"wp-element-caption\">Fig:1 Photorealistic avatars captured by complex system of camera arrays<\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"has-text-align-left\">The goal of this project is simplify avatar creation by using smartphone data with RGBD sensors, eliminating the need for complex camera arrays shown in Fig 1. This approach enhances scalability and adoption of avatars, as illustrated in Fig 2.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"760\" height=\"424\" src=\"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Avatar.png\" alt=\"\" class=\"wp-image-53\" style=\"width:428px;height:auto\" srcset=\"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Avatar.png 760w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Avatar-300x167.png 300w\" sizes=\"auto, (max-width: 706px) 89vw, (max-width: 767px) 82vw, 740px\" \/><figcaption class=\"wp-element-caption\">Fig:2 Creation of avatars from mobile phone data<br><\/figcaption><\/figure>\n<\/div>\n\n\n<p class=\"has-text-align-left\">Thus, our problem statement boils down to,<\/p>\n\n\n\n<blockquote class=\"wp-block-quote has-text-align-center is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"has-text-align-left\"><em><mark style=\"background-color:#fde29a\" class=\"has-inline-color\"><strong>Real-time<\/strong> and <strong>Online <\/strong>reconstruction of <strong>dynamic scenes<\/strong> with <strong>non-rigid motion<\/strong> from <strong>monocular<\/strong> RGB-D videos (e.g. from an iPhone) for <strong>flexible<\/strong> and <strong>interactive<\/strong> engagement.<\/mark><\/em><\/p>\n<\/blockquote>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"240\" src=\"http:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Teaser-1024x240.png\" alt=\"\" class=\"wp-image-54\" srcset=\"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Teaser-1024x240.png 1024w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Teaser-300x70.png 300w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Teaser-768x180.png 768w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Teaser-1536x360.png 1536w, https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/wp-content\/uploads\/sites\/101\/2024\/05\/Teaser-2048x481.png 2048w\" sizes=\"auto, (max-width: 706px) 89vw, (max-width: 767px) 82vw, 740px\" \/><figcaption class=\"wp-element-caption\">Fig:3 Our system takes an input RGB-D time sequence to reconstruct the dynamic scene and render novel views.<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>The goal of this project is simplify avatar creation by using smartphone data with RGBD sensors, eliminating the need for complex camera arrays shown in Fig 1. This approach enhances scalability and adoption of avatars, as illustrated in Fig 2. Thus, our problem statement boils down to, Real-time and Online reconstruction of dynamic scenes with &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/introduction\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Introduction&#8221;<\/span><\/a><\/p>\n","protected":false},"author":197,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Introduction - Dynamic Reconstruction of Non-rigid Scenes from Monocular RGB-D Videos<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mscvprojects.ri.cmu.edu\/2024team3\/introduction\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Introduction - Dynamic Reconstruction of Non-rigid Scenes from Monocular RGB-D Videos\" \/>\n<meta property=\"og:description\" content=\"The goal of this project is simplify avatar creation by using smartphone data with RGBD sensors, eliminating the need for complex camera arrays shown in Fig 1. 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