We investigate the problem of stitching timely synchronized video streams captured by freely moving devices. Recently, it was shown that using frame-to-frame correlation can greatly enhance the efficiency and effectiveness of video stitching algorithms \u200e[19]. In this paper, we address some of the shortcomings in \u200e[19], namely the simple blending approach, causing almost a third of stitching errors and the fact that the stitching algorithm is only tested on a frame-by-frame basis which does not realistically mimic the user perception of the output system quality as a complete video. We propose the use of a modified blending technique based on optimal seam selection and experimentally validate its superiority using precision, recall and F1 measures on a frame-by-frame basis, while maintaining low computational complexity.\u00a0 Furthermore, we validate that the performance gains measured on a frame-by-frame basis are also evident when the stitched video output is evaluated as a single unit.<\/p>\n","protected":false},"excerpt":{"rendered":"
We investigate the problem of stitching timely synchronized video streams captured by freely moving devices. Recently, it was shown that using frame-to-frame correlation can greatly enhance the efficiency and effectiveness of video stitching algorithms \u200e[19]. In this paper, we address some of the shortcomings in \u200e[19], namely the simple blending approach, causing almost a third […]<\/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","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"ICIP","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":"ICIP","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Mostafa Izz, Mahmoud Refaat","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2011-01-01","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":2011,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13562],"msr-publication-type":[193716],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-161394","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-computer-vision","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"ICIP","msr_affiliation":"","msr_published_date":"2011-01-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"206722","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"paper_blending_cameraReady.pdf","viewUrl":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/wp-content\/uploads\/2016\/02\/paper_blending_cameraReady.pdf","id":206722,"label_id":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[{"id":206722,"url":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/wp-content\/uploads\/2016\/02\/paper_blending_cameraReady.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"motazel","user_id":33004,"rest_url":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=motazel"},{"type":"text","value":"Mostafa Izz","user_id":0,"rest_url":false},{"type":"user_nicename","value":"aymank","user_id":31161,"rest_url":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=aymank"},{"type":"text","value":"Mahmoud Refaat","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[170355],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":170355,"post_title":"Mobicast","post_name":"mobicast","post_type":"msr-project","post_date":"2009-11-05 09:02:08","post_modified":"2017-05-31 12:02:11","post_status":"publish","permalink":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/project\/mobicast\/","post_excerpt":"The aim of this project is to enable the collaboration between multiple users casting the same event from their mobile phones to provide a better collective viewing experience of the event to end viewers. 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