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Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis
Speaker:Wei Zheng
Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, and Yingcai Wu
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Introduction
2
why• Previous
tools are hard to use
• Not effective for tactic
what• A tool easy to
use and understand;
• A model for tactic;
how• A visualization
tool; • 2nd order
Markov chain model ;
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Table tennis match structure
[Fig 2. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
match
games rallies stroke
tactic
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● Collected manually
● 9 kinds of stroke placement
● 13 kinds of stroke technique
● 4 kinds of stroke position
Data
[Table 1. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
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[Fig 1. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
The overview of the Tac-Simur system
Data processing
Model
Visualization
● Navigation: locate data ● Exploration: support adjustments ● Explanation: provides a
straightforward presentation
Expert requirements
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Model for simulation
[Fig 2. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
𝐺𝑖 = {𝑅𝑖1, 𝑅𝑖
2, …, 𝑅𝑖𝑛}
𝑅𝑖𝑗 = {𝑆𝑖,𝑗
1 , 𝑆𝑖,𝑗2 , …, 𝑆𝑖,𝑗
𝑛 , 𝑃𝑖𝑗} Simulate the stroke sequence
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The First-order VS the Second-order Markov Chain Model
Original model new model.
[Fig 3. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
● Inadequate Tactic Modeling
- considering 2 previous strokes in 2nd order Markov chain model
● Insufficient Stroke Characterization
-expanded the number of attributes used in stroke characterization to three
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The First-order VS the Second-order Markov Chain Model
Original model New model
[Fig 3. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
· + ·𝑉𝑘 = λ1 · V𝑘−1 T1 λ2 · V𝑘−2 T2 • The different phases in a rally are simulated
by different Markov processes.
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[Fig 4. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
Model evaluation
● Higher recall rates ● Higher precision
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[Fig 5. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
System design
Main view
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[Fig 6. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
System design
Explanation view
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Let’s watch a video showing system in action
12
https://www.youtube.com/watch?v=_I6cne3Wd4U
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System evaluation
[Fig 7. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
Step1: find pattern in tech view
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System evaluation
[Fig 7. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
Step2: Generate optimum strategy
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System evaluation
[Fig 7. Tac-Simur: Tactic-based Simulative Visual Analytics of Table Tennis. Jiachen Wang, Kejian Zhao, Dazhen Deng, Anqi Cao, Xiao Xie, Zheng Zhou, Hui Zhang, Yingcai Wu. IEEE Trans. Visualization and Computer Graphics (Proc. Vis 2019), 26(1):407-417, 2019.]
Step3: Check explanation
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Analysis summary
• What: data Table of strokes
• How: encode Color, spatial, node-link Bar, glyphs
• How: change animation
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Critique
Strengths:
• Provide a suitable model for the simulative analysis of table tennis;
• Design a user-friendly visualization tool.
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Critique
Weaknesses: • Fail to give proof why Markov chain is better than deep
learning; • Three features for strokes are not enough, should have
the force of the stroke, rotation speed of the ball • The way to encode stroke position is not intuitive
forehand backhand Backhand turn Pivot
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Thanks!