{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/129862"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/129862","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multimodal content analysis and streaming in multiview environment","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms","abstract_has_math":false,"creators":["Lee, Kuan-Ying"],"institution":"University of Illinois Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Nahrstedt, Klara","Wang, Yu-Xiong","Do, Minh","Cesar, Pablo"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-07-11","date_published":"2025-07-11","updated_at":"2026-07-22T22:25:06Z","subjects":["Learning-based Methods","Multiview","Multimodal","Streaming"],"languages":["en","eng"],"rights":["Copyright 2025 Kuan-Ying Lee"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/129862","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nahrstedt, Klara","Wang, Yu-Xiong","Do, Minh","Cesar, Pablo"]},{"key":"dc:creator","label":"Author","values":["Lee, Kuan-Ying"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-07-11","2025-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Learning-based Methods","Multiview","Multimodal","Streaming"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Kuan-Ying Lee"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/129862"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms","The student, Kuan-Ying Lee, accepted the attached license on 2025-07-10 at 20:51.","The student, Kuan-Ying Lee, submitted this Dissertation for approval on 2025-07-10 at 21:04.","This Dissertation was approved for publication on 2025-07-11 at 09:41.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22498 on 2025-10-20 at 16:57:45","A multiview environment where cameras are deployed to capture the same scene is essential in countless applications. However, the complexity of its content analysis and delivery requires intricate design. The complexities could be summarized into two folds: 1) what to deliver at every timestamp, and 2) how to deliver under the constraint of bandwidth. This thesis attempts to leverage learning-based algorithms to analyze the multimodal cues, including visual and audio cues, in the multiview environment to help multiview content delivery that satisfies audience preferences and needs. Based on the nature of multiview content, we divide the research scope into on-demand and real-time content analysis and delivery. We start from on-demand multiview content analysis, study multi-camera view recommendation, and move on to on-demand content delivery of 360◦ videos. Then, considering the capricious characteristics of real-time multiview content, we investigate how continual learning on pre-trained models could aid in its analysis. Finally, we investigate speaking intent detection in 360◦ video streaming, which could be leveraged to distribute limited bandwidth over 360◦ video frames and deliver a more immersive experience in virtual reality meetings. Different aspects investigated in this thesis could provide insights into how various types of multi-view content could be analyzed and delivered to satisfy users’ potential multi-faceted needs."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Multimodal content analysis and streaming in multiview environment"]}]}],"canonical_facts":{"dc:contributor":["Nahrstedt, Klara","Wang, Yu-Xiong","Do, Minh","Cesar, Pablo"],"dc:creator":["Lee, Kuan-Ying"],"dc:date":["2025-07-11","2025-08"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms","The student, Kuan-Ying Lee, accepted the attached license on 2025-07-10 at 20:51.","The student, Kuan-Ying Lee, submitted this Dissertation for approval on 2025-07-10 at 21:04.","This Dissertation was approved for publication on 2025-07-11 at 09:41.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22498 on 2025-10-20 at 16:57:45","A multiview environment where cameras are deployed to capture the same scene is essential in countless applications. However, the complexity of its content analysis and delivery requires intricate design. The complexities could be summarized into two folds: 1) what to deliver at every timestamp, and 2) how to deliver under the constraint of bandwidth. This thesis attempts to leverage learning-based algorithms to analyze the multimodal cues, including visual and audio cues, in the multiview environment to help multiview content delivery that satisfies audience preferences and needs. Based on the nature of multiview content, we divide the research scope into on-demand and real-time content analysis and delivery. We start from on-demand multiview content analysis, study multi-camera view recommendation, and move on to on-demand content delivery of 360◦ videos. Then, considering the capricious characteristics of real-time multiview content, we investigate how continual learning on pre-trained models could aid in its analysis. Finally, we investigate speaking intent detection in 360◦ video streaming, which could be leveraged to distribute limited bandwidth over 360◦ video frames and deliver a more immersive experience in virtual reality meetings. Different aspects investigated in this thesis could provide insights into how various types of multi-view content could be analyzed and delivered to satisfy users’ potential multi-faceted needs."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/129862"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Kuan-Ying Lee"],"dc:subject":["Learning-based Methods","Multiview","Multimodal","Streaming"],"dc:title":["Multimodal content analysis and streaming in multiview environment"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:06Z"}