A survey of competitive sports data visualization and visual analysis
Competitive sports data visualization is an increasingly important research direction in the field of information visualization. It is also an important basis for studying human behavioral pattern and activity habits. In this paper, we provide a taxonomy of sports data visualization and summarize th...
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| Published in | Journal of visualization Vol. 24; no. 1; pp. 47 - 67 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.02.2021
Springer Nature B.V |
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| Online Access | Get full text |
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| Abstract | Competitive sports data visualization is an increasingly important research direction in the field of information visualization. It is also an important basis for studying human behavioral pattern and activity habits. In this paper, we provide a taxonomy of sports data visualization and summarize the state-of-the-art research from four aspects of data types, main tasks and visualization techniques and visual analysis. Specifically, we first put sports data into two categories: spatiotemporal information and statistical information. Then, we propose three main tasks for competitive sports data visualization: feature presentation, feature comparison and feature prediction. Furthermore, we classify competitive sports data visualization techniques based on data characteristics into five categories: high-dimensional data visualization, time-series visualization, graph (network) visualization, glyph visualization and other visualization, and we analyze the relationship between major tasks and visualization techniques. We also introduce visual analysis research work of competitive sports, propose the features and limitations of competitive sports data, summarize multimedia visualization in competitive sports and finally discuss visual analysis evaluation. In this survey, we attempt to help readers to find appropriate techniques for different data types and different tasks. Our paper also intends to provide guidelines and references for future researchers when they study human behavior and moving patterns.
Graphic abstract |
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| AbstractList | Competitive sports data visualization is an increasingly important research direction in the field of information visualization. It is also an important basis for studying human behavioral pattern and activity habits. In this paper, we provide a taxonomy of sports data visualization and summarize the state-of-the-art research from four aspects of data types, main tasks and visualization techniques and visual analysis. Specifically, we first put sports data into two categories: spatiotemporal information and statistical information. Then, we propose three main tasks for competitive sports data visualization: feature presentation, feature comparison and feature prediction. Furthermore, we classify competitive sports data visualization techniques based on data characteristics into five categories: high-dimensional data visualization, time-series visualization, graph (network) visualization, glyph visualization and other visualization, and we analyze the relationship between major tasks and visualization techniques. We also introduce visual analysis research work of competitive sports, propose the features and limitations of competitive sports data, summarize multimedia visualization in competitive sports and finally discuss visual analysis evaluation. In this survey, we attempt to help readers to find appropriate techniques for different data types and different tasks. Our paper also intends to provide guidelines and references for future researchers when they study human behavior and moving patterns.
Graphic abstract Competitive sports data visualization is an increasingly important research direction in the field of information visualization. It is also an important basis for studying human behavioral pattern and activity habits. In this paper, we provide a taxonomy of sports data visualization and summarize the state-of-the-art research from four aspects of data types, main tasks and visualization techniques and visual analysis. Specifically, we first put sports data into two categories: spatiotemporal information and statistical information. Then, we propose three main tasks for competitive sports data visualization: feature presentation, feature comparison and feature prediction. Furthermore, we classify competitive sports data visualization techniques based on data characteristics into five categories: high-dimensional data visualization, time-series visualization, graph (network) visualization, glyph visualization and other visualization, and we analyze the relationship between major tasks and visualization techniques. We also introduce visual analysis research work of competitive sports, propose the features and limitations of competitive sports data, summarize multimedia visualization in competitive sports and finally discuss visual analysis evaluation. In this survey, we attempt to help readers to find appropriate techniques for different data types and different tasks. Our paper also intends to provide guidelines and references for future researchers when they study human behavior and moving patterns.Graphic abstract |
| Author | Yuan, Xiaoru Du, Meng |
| Author_xml | – sequence: 1 givenname: Meng orcidid: 0000-0002-6050-2737 surname: Du fullname: Du, Meng organization: School of New Media, Beijing Institution of Graphic Communication, International New Media Institution of Industry-Education-Research Cooperation, Key Laboratory of Machine Perception (Ministry of Education), School of EECS, and Center for Computational Science and Engineering, Peking University – sequence: 2 givenname: Xiaoru surname: Yuan fullname: Yuan, Xiaoru email: xiaoru.yuan@pku.edu.cn organization: Key Laboratory of Machine Perception (Ministry of Education), School of EECS, and Center for Computational Science and Engineering, Peking University, National Engineering Laboratory for Big Data Analysis and Application and Beijing Engineering Technology Research Center of Virtual Simulation and Visualization, Peking University |
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| Snippet | Competitive sports data visualization is an increasingly important research direction in the field of information visualization. It is also an important basis... |
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| SubjectTerms | Classical and Continuum Physics Computer Imaging Data analysis Engineering Engineering Fluid Dynamics Engineering Thermodynamics Heat and Mass Transfer Multimedia Pattern Recognition and Graphics Regular Paper Scientific visualization Sports Taxonomy Vision Visualization |
| Title | A survey of competitive sports data visualization and visual analysis |
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