We propose a system to transform any temporal image sequence into a comics-based presentation, as an effective and interesting storytelling manner. Three main components, including page allocation, layout selection, and speech balloon placement, are respectively formulated as optimization problems, and systematic approaches are proposed to find solutions. Page allocation is viewed as a labeling problem, and the best solution is determined by the genetic algorithm. Importance values of images and predefined layouts are both represented in vector forms, and the best layout is selected by finding the best match between vectors. Feasible solutions of speech balloons constitute a solution space, and the best solution that jointly describes the best locations of all balloons in a page is determined by the particle swarm optimization algorithm. Objective evaluation and subjective evaluation are designed from various perspectives to demonstrate effectiveness and superiority of the proposed system.Index Terms-Comics-based storytelling, genetic algorithm, layout selection, page allocation, particle swarm optimization, speech balloon placement.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.