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SmartShots: An Optimization Approach for Generating Videos with Data Visualizations Embedded

Authors :
Tan Tang
Junxiu Tang
Jiewen Lai
Lu Ying
Yingcai Wu
Lingyun Yu
Peiran Ren
Source :
ACM Transactions on Interactive Intelligent Systems. 12:1-21
Publication Year :
2022
Publisher :
Association for Computing Machinery (ACM), 2022.

Abstract

Videos are well-received methods for storytellers to communicate various narratives. To further engage viewers, we introduce a novel visual medium where data visualizations are embedded into videos to present data insights. However, creating such data-driven videos requires professional video editing skills, data visualization knowledge, and even design talents. To ease the difficulty, we propose an optimization method and develop SmartShots, which facilitates the automatic integration of in-video visualizations. For its development, we first collaborated with experts from different backgrounds, including information visualization, design, and video production. Our discussions led to a design space that summarizes crucial design considerations along three dimensions: visualization, embedded layout, and rhythm. Based on that, we formulated an optimization problem that aims to address two challenges: (1) embedding visualizations while considering both contextual relevance and aesthetic principles and (2) generating videos by assembling multi-media materials. We show how SmartShots solves this optimization problem and demonstrate its usage in three cases. Finally, we report the results of semi-structured interviews with experts and amateur users on the usability of SmartShots.

Details

ISSN :
21606463 and 21606455
Volume :
12
Database :
OpenAIRE
Journal :
ACM Transactions on Interactive Intelligent Systems
Accession number :
edsair.doi...........4eab00595f51c25a0e6242cadfec477c
Full Text :
https://doi.org/10.1145/3484506