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BEGIN:VEVENT
DTSTAMP:20230103T035307Z
LOCATION:Auditorium\, Level 5\, West Wing
DTSTART;TZID=Asia/Seoul:20221206T100000
DTEND;TZID=Asia/Seoul:20221206T120000
UID:siggraphasia_SIGGRAPH Asia 2022_sess153_papers_289@linklings.com
SUMMARY:PopStage: The Generation of Stage Cross-Editing Video based on Spa
 tio-Temporal Matching
DESCRIPTION:Technical Papers\n\nPopStage: The Generation of Stage Cross-Ed
 iting Video based on Spatio-Temporal Matching\n\nLee, Yoo, Cho, Kim, Im...
 \n\nStageMix is a mixed video that is created by concatenating the segment
 s from various performance videos of an identical song in a visually smoot
 h manner by matching the main subject's silhouette presented in the frame.
  We introduce PopStage, which allows users to generate a StageMix automati
 cally. PopStage is designed based on the StageMix Editing Guideline that w
 e established by interviewing creators as well as observing their workflow
 s. PopStage consists of two main steps: finding an editing path and genera
 ting a transition effect at a transition point. Using a reward function th
 at favors visual connection and the optimality of transition timing across
  the videos, we obtain the optimal path that maximizes the sum of rewards 
 through dynamic programming. Given the optimal path, PopStage then aligns 
 the silhouettes of the main subject from the transitioning video pair to e
 nhance the visual connection at the transition point. The virtual camera v
 iew is next optimized to remove the black areas that are often created due
  to the transformation needed for silhouette alignment, while reducing pix
 el loss. In this process, we enforce the view to be the maximum size while
  maintaining the temporal continuity across the frames. Experimental resul
 ts show that PopStage can generate a StageMix of a similar quality to thos
 e produced by professional creators in a highly reduced production time.\n
 \nRegistration Category: FULL ACCESS, EXPERIENCE PLUS ACCESS, EXPERIENCE A
 CCESS, TRADE EXHIBITOR\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_289&sess=sess15
 3
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