PlotThread : Creating Expressive Storyline Visualizations using Reinforcement Learning

Storyline visualizations are an effective means to present the evolution of plots and reveal the scenic interactions among characters. However, the design of storyline visualizations is a difficult task as users need to balance between aesthetic goals and narrative constraints. Despite that the opti...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 27(2021), 2 vom: 13. Feb., Seite 294-303
1. Verfasser: Tang, Tan (VerfasserIn)
Weitere Verfasser: Li, Renzhong, Wu, Xinke, Liu, Shuhan, Knittel, Johannes, Koch, Steffen, Yu, Lingyun, Ren, Peiran, Ertl, Thomas, Wu, Yingcai
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article
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520 |a Storyline visualizations are an effective means to present the evolution of plots and reveal the scenic interactions among characters. However, the design of storyline visualizations is a difficult task as users need to balance between aesthetic goals and narrative constraints. Despite that the optimization-based methods have been improved significantly in terms of producing aesthetic and legible layouts, the existing (semi-) automatic methods are still limited regarding 1) efficient exploration of the storyline design space and 2) flexible customization of storyline layouts. In this work, we propose a reinforcement learning framework to train an AI agent that assists users in exploring the design space efficiently and generating well-optimized storylines. Based on the framework, we introduce PlotThread, an authoring tool that integrates a set of flexible interactions to support easy customization of storyline visualizations. To seamlessly integrate the AI agent into the authoring process, we employ a mixed-initiative approach where both the agent and designers work on the same canvas to boost the collaborative design of storylines. We evaluate the reinforcement learning model through qualitative and quantitative experiments and demonstrate the usage of PlotThread using a collection of use cases 
650 4 |a Journal Article 
700 1 |a Li, Renzhong  |e verfasserin  |4 aut 
700 1 |a Wu, Xinke  |e verfasserin  |4 aut 
700 1 |a Liu, Shuhan  |e verfasserin  |4 aut 
700 1 |a Knittel, Johannes  |e verfasserin  |4 aut 
700 1 |a Koch, Steffen  |e verfasserin  |4 aut 
700 1 |a Yu, Lingyun  |e verfasserin  |4 aut 
700 1 |a Ren, Peiran  |e verfasserin  |4 aut 
700 1 |a Ertl, Thomas  |e verfasserin  |4 aut 
700 1 |a Wu, Yingcai  |e verfasserin  |4 aut 
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