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.

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animated motion animating still manga imagery mood datadriven graphical model domain knowledge human efforts film production genres animations story method lowlevel visual patterns camera movements characteristics of manga mobile comic reading and comic trailer generation storytelling and pacing perpanel motion and emotion states

Rynson W. H. Lau,Ying Cao, Antoni B. Chan, Xufang Pang,.Dynamic Manga: Animating Still Manga via Camera Movement. 19 (1),160-172.

Rynson W. H. Lau, et al."Dynamic Manga: Animating Still Manga via Camera Movement" 19

Rynson W. H. Lau,Ying Cao, Antoni B. Chan, Xufang Pang,"Dynamic Manga: Animating Still Manga via Camera Movement"