Emotion Transfer for Hand Animation

Ana-Sabina Irimia, Jacky C. P. Chan, Kamlesh Mistry, Wei Wei, Edmond S. L. Ho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)
12 Downloads (Pure)


We propose a new data-driven framework for synthesizing hand motion at different emotion levels. Specifically, we first capture high-quality hand motion using VR gloves. The hand motion data is then annotated with the emotion type and a latent space is constructed from the motions to facilitate the motion synthesis process. By interpolating the latent representation of the hand motion, new hand animation with different levels of emotion strength can be generated. Experimental results show that our framework can produce smooth and consistent hand motions at an interactive rate.
Original languageEnglish
Title of host publicationProceedings - MIG 2019: ACM Conference on Motion, Interaction, and Games
Subtitle of host publicationNewcastle upon Tyne, England, October 28-30, 2019
EditorsHubert P. H. Shum, Edmond S. L. Ho, Marie-Paule Cani, Tiberiu Popa, Daniel Holden, He Wang
Place of PublicationNew York
ISBN (Electronic)9781450369947
Publication statusPublished - 28 Oct 2019
EventMIG 2019: 12th annual ACM/SIGGRAPH conference on Motion, Interaction and Games - Northumbria University, Newcastle upon Tyne, United Kingdom
Duration: 28 Oct 201930 Oct 2019


ConferenceMIG 2019
Country/TerritoryUnited Kingdom
CityNewcastle upon Tyne
Internet address


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