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EAGER: Investigation of Techniques for Creating Storytelling Animations During Data Exploration

EAGER: Investigation of Techniques for Creating Storytelling Animations During Data Exploration
EAGER:在数据探索过程中创建讲故事动画的技术研究
批准号:
1255237
负责人:
Kwan-Liu Ma
金额:
$9.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-10-01 至 2014-09-30

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中文摘要
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英文摘要
The aim of this exploratory project is to enable scientists to easily create storytelling animations for effective communication of research results. Today visualization has become an indispensable tool for many scientists in their daily work to validate and explore the data obtained from their studies, to discover new findings, and to communicate them with others. Both commercial and open-source visualization tools offer a wealth of visualization techniques, enabling scientists to explore their data and generate individual images which capture key aspects of the subject under study. However, an important need of scientists - creating animations for storytelling - is not sufficiently supported. Scientists make extensive use of animation in the form of videos that explain complex structures or processes. Surprisingly, most visualization packages provide very limited support for making animations. The objectives of this project are to: (1) design an interactive animation interface seamlessly integrated with the visualization interface, and develop optimal strategies for controlling camera movement based on key-frames specified by the user; (2) create a prototype system to assess how well the proposed integrated interface enhances users' ability to create visualization animations for storytelling; and (3) through case studies and a user study, investigate whether animations created using the system effectively illustrate complex processes and spatial relationships. This proof-of-concept study focuses on volume data visualization; however, the results are expected to be generalizable to a wide range of scientific and information visualization. This proposed research is challenging as it seeks to establish understanding of how animations can effectively illustrate evolving structures, spatial relationships, and patterns and what system support is needed to enable users to create expressive animations during data exploration without seeking help from professional animators.The lessons learned in this study suggest the design of a new framework for next-generation visualization systems that can benefit a broad range of scientists. Educational activities include the integration of research into teaching, in the form of special topic courses, the establishment of internships with industry and national laboratories, and the introduction of the proposed visualization technology to students from other disciplines. Project website (http://vis.cs.ucdavis.edu/NSF/IIS1255237) is used for results dissemination.
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