{"id":168379,"date":"2015-01-01T00:00:00","date_gmt":"2015-01-01T00:00:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/resolving-multipath-interference-in-kinect-an-inverse-problem-approach\/"},"modified":"2018-10-16T20:17:25","modified_gmt":"2018-10-17T03:17:25","slug":"resolving-multipath-interference-in-kinect-an-inverse-problem-approach","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/resolving-multipath-interference-in-kinect-an-inverse-problem-approach\/","title":{"rendered":"Resolving Multipath Interference in Kinect: An Inverse Problem Approach"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Multipath interference (MPI) is one of the major sources of both depth and amplitude measurement errors in Time\u2013of\u2013Flight (ToF) cameras. This problem has seen a lot of attention recently. In this work, we discuss the MPI problem within the framework spectral estimation theory and multi\u2013 frequency measurements. As compared to previous approaches that consider up to two interfering paths, our model considers the general case of <em>K<\/em> \u2013interfering paths. In the theoretical setting, we show that for the case of <em>K<\/em>\u2013interfering paths of light, 2<em>K<\/em> +1 frequency measurements suffice to recover the depth and amplitude values corresponding to each of the <em>K<\/em> optical paths. What singles out our method is the that our algorithm is non\u2013iterative in implementation. This leads to a closed\u2013form solution which is computationally attractive. Also, for the first time, we demonstrate the effectiveness of our model on an off\u2013 the\u2013shelf Microsoft Kinect for the X\u2013Box one.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Multipath interference (MPI) is one of the major sources of both depth and amplitude measurement errors in Time\u2013of\u2013Flight (ToF) cameras. This problem has seen a lot of attention recently. In this work, we discuss the MPI problem within the framework spectral estimation theory and multi\u2013 frequency measurements. As compared to previous approaches that consider up [&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":"IEEE Sensors","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","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":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Ayush Bhandari, Micha Feigin, Mirko Schmidt, Ramesh 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