Wakey-Wakey: Animate Text by Mimicking Characters in a GIF

要旨

With appealing visual effects, kinetic typography (animated text) has prevailed in movies, advertisements, and social media. However, it remains challenging and time-consuming to craft its animation scheme. We propose an automatic framework to transfer the animation scheme of a rigid body on a given meme GIF to text in vector format. First, the trajectories of key points on the GIF anchor are extracted and mapped to the text's control points based on local affine transformation. Then the temporal positions of the control points are optimized to maintain the text topology. We also develop an authoring tool that allows intuitive human control in the generation process. A questionnaire study provides evidence that the output results are aesthetically pleasing and well preserve the animation patterns in the original GIF, where participants were impressed by a similar emotional semantics of the original GIF. In addition, we evaluate the utility and effectiveness of our approach through a workshop with general users and designers.

著者
Zhaoyu Zhou
Fudan University, Shanghai, China
Liwenhan Xie
The Hong Kong University of Science and Technology, Hong Kong, China
Kerun Yu
Fudan University, Shanghai, China
Yun Wang
Microsoft Research Asia, Beijing, China
Huamin Qu
The Hong Kong University of Science and Technology, Hong Kong, China
Siming Chen
Fudan University, Shanghai, China
論文URL

https://doi.org/10.1145/3586183.3606813

動画

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Words and Visuals: Authoring Tools for Text and Images

Gold Room
6 件の発表
2023-11-01 19:50:00
2023-11-01 21:10:00