Name
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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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3180308.3180359 | COMPANION OF THE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT USER INTERFACES (IUI'18) |
Keywords | Field | DocType |
Gaze analysis, Data clustering, Gaze data visualization | Unconscious mind,Data processing,Gaze,Computer science,Visualization,Human–computer interaction,Cluster analysis,Area of interest | Conference |
ISBN | Citations | PageRank |
978-1-4503-5571-1 | 0 | 0.34 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sangbong Yoo | 1 | 0 | 2.37 |
| Sujin Jeong | 2 | 0 | 0.34 |
| Yun Jang | 3 | 302 | 25.63 |