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Mining attention distribution paradigm: Discover gaze patterns and their association rules behind the visual image
Weiwei Yu1, Feng Zhao2, Zhijun Ren2
1School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, 710072, China; Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an, 710072, China.
Computer Methods and Programs in Biomedicine
|January 5, 2023
Summary
This study introduces a big data mining approach to analyze visual attention patterns. The method reveals frequent eye movement patterns and their associations within complex tasks, offering insights into attention distribution.
Area of Science:
- Cognitive Science
- Data Mining
- Human-Computer Interaction
Background:
- Visual attention is crucial for information processing and is influenced by task scenarios.
- Existing methods for analyzing visual attention lack insight into gaze behavior within context and association rules.
- A novel big data mining approach is needed to understand attention distribution patterns.
Purpose of the Study:
- To discover visual attention distribution patterns using a big data mining approach.
- To reveal regularities of attention distribution behavior within specific task scenarios.
- To identify association rules of visual attention patterns.
Main Methods:
- Applied data mining techniques to extract gaze patterns.
- Segmented and clustered task scenarios using a TICC-based method.
- Employed frequent pattern mining to discover association rules.
Main Results:
- Successfully extracted frequent eye movement patterns and their association rules.
- Demonstrated the method's ability to link eye-tracking data with task-oriented scene data.
- Validated the approach on a complex operation task using the BCI index.
Conclusions:
- The proposed method enables explicit expression and quantitative analysis of visual attention patterns.
- Potential applications include aerospace medicine, aviation psychology, and computer-aided diagnosis for neurological and cognitive disorders.
- The approach can aid in the follow-up of conditions like ADHD, neglect syndrome, and ASD.
