TY - GEN
T1 - Pose2Pose
AU - Willett, Nora S.
AU - Shin, Hijung Valentina
AU - Jin, Zeyu
AU - Li, Wilmot
AU - Finkelstein, Adam
N1 - Publisher Copyright:
© ACM.
PY - 2020/3/17
Y1 - 2020/3/17
N2 - An artist faces two challenges when creating a 2D animated character to mimic a specific human performance. First, the artist must design and draw a collection of artwork depicting portions of the character in a suitable set of poses, for example arm and hand poses that can be selected and combined to express the range of gestures typical for that person. Next, to depict a specific performance, the artist must select and position the appropriate set of artwork at each moment of the animation. This paper presents a system that addresses these challenges by leveraging video of the target human performer. Our system tracks arm and hand poses in an example video of the target. The UI displays clusters of these poses to help artists select representative poses that capture the actor's style and personality. From this mapping of pose data to character artwork, our system can generate an animation from a new performance video. It relies on a dynamic programming algorithm to optimize for smooth animations that match the poses found in the video. Artists used our system to create four 2D characters and were pleased with the final automatically animated results. We also describe additional applications addressing audio-driven or text-based animations.
AB - An artist faces two challenges when creating a 2D animated character to mimic a specific human performance. First, the artist must design and draw a collection of artwork depicting portions of the character in a suitable set of poses, for example arm and hand poses that can be selected and combined to express the range of gestures typical for that person. Next, to depict a specific performance, the artist must select and position the appropriate set of artwork at each moment of the animation. This paper presents a system that addresses these challenges by leveraging video of the target human performer. Our system tracks arm and hand poses in an example video of the target. The UI displays clusters of these poses to help artists select representative poses that capture the actor's style and personality. From this mapping of pose data to character artwork, our system can generate an animation from a new performance video. It relies on a dynamic programming algorithm to optimize for smooth animations that match the poses found in the video. Artists used our system to create four 2D characters and were pleased with the final automatically animated results. We also describe additional applications addressing audio-driven or text-based animations.
KW - 2D character creation
KW - animation
KW - pose selection
UR - http://www.scopus.com/inward/record.url?scp=85082449344&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082449344&partnerID=8YFLogxK
U2 - 10.1145/3377325.3377505
DO - 10.1145/3377325.3377505
M3 - Conference contribution
AN - SCOPUS:85082449344
T3 - International Conference on Intelligent User Interfaces, Proceedings IUI
SP - 88
EP - 99
BT - Proceedings of the 25th International Conference on Intelligent User Interfaces, IUI 2020
PB - Association for Computing Machinery
T2 - 25th ACM International Conference on Intelligent User Interfaces, IUI 2020
Y2 - 17 March 2020 through 20 March 2020
ER -