U-GMo: Individual Clip Detection from a Graduation Ceremony Video

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dc.contributor.authorTreesoonrat, Natee
dc.contributor.authorKriengchaiyaprug, Nunnapat
dc.contributor.authorUpadhayawong, Thanakann
dc.contributor.authorLohapongpan, Warinya
dc.contributor.authorChawuthai, Rathachai
dc.contributor.authorCherntanomwong, Panarat
dc.date.accessioned2026-08-06T10:43:57Z
dc.date.available2026-08-06T10:43:57Z
dc.date.issued2024-01-01
dc.description.abstractGraduation ceremonies are important occasions in life. A video in this event is usually very long due to a lot of graduates getting their degree. This study suggests a method for automatically cutting the entire ceremony video into customized segments that only include the most significant events for each particular graduate, named U-GMo (Your Great Moment). The system uses deep learning with computer vision techniques, such as YOLOv8 for posture detection, to identify graduates by observing their motions and posture during the degree ceremony. After that, the identified bits are taken out and assembled into brief video snippets for every graduate. The algorithm can detect and extract each graduate's crucial moments with high performance, according to an examination conducted on a dataset of graduation ceremonies. The personalized video clips provide a convenient way to preserve the meaningful highlights from these milestone events.
dc.identifier.citation2024 International Technical Conference on Circuits Systems Computers and Communications Itc Cscc 2024, 2024
dc.identifier.doi10.1109/ITC-CSCC62988.2024.10628160
dc.identifier.other2-s2.0-85203606910
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/15070
dc.source2024 International Technical Conference on Circuits Systems Computers and Communications Itc Cscc 2024
dc.subjectArtificial Intelligence
dc.subjectDeep Learning
dc.subjectGraduation Ceremony
dc.subjectPosture Detection
dc.subjectVideo Processing
dc.subjectYOLOv8
dc.titleU-GMo: Individual Clip Detection from a Graduation Ceremony Video
dc.typeConference Paper

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