We propose a method for animating still manga
imagery through camera movements. Given a series of existing
manga pages, we start by automatically extracting panels, comic
characters and balloons from the manga pages. Then, we use
a data-driven graphical model to infer per-panel motion and
emotion states from low-level visual patterns. Finally, by combining
domain knowledge of film production and characteristics
of manga, we simulate camera movements over the manga pages,
yielding an animation. The results augment the still manga
contents with animated motion that reveals the mood and tension
of the story, while maintaining the original narrative. We have
tested our method on manga series of different genres, and
demonstrated that our method can generate animations that are
more effective in storytelling and pacing, with less human efforts,
as compared with prior works. We also show two applications of
our method, mobile comic reading and comic trailer generation.
@article{Cao2016,
author = {Y. Cao and Xufang Pang and R. Lau and A. B. Chan},
title = {DynamicManga: Animating Still Manga via Camera Movement},
journal = {IEEE Transactions on Multimedia},
year = {2016}
}