Sangbong Yoo
ABSTRACT
Eye-Gaze contains useful information, especially, unconscious intention of human. However, it is difficult to distinguish between noise and intentional or unconscious movement from the gaze data. Moreover, matching stimuli with the data is not easy since many Area of Interest (AoI) clustering algorithms generate unwanted information. Therefore, the gaze data analysis and utilization are still limited. The intentions in the gaze data can be categorized as navigational and informational. Hence, different visualization technique and analysis should be applied for each intention. In this paper, we study gaze data analysis using various data processing techniques, such as cluster and filter with corresponding visualization.
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Index Terms
- Gaze Data Clustering and Analysis
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