Name
Abstract | ||
|---|---|---|
Pupil diameter changes have been shown to be indicative of user engagement and cognitive load for various tasks and environments. However, it is still not the preferred physiological measure for applied settings. This reluctance to leverage the pupil as an index of user engagement stems from the problem that in scenarios where scene brightness cannot be controlled, the pupil light response confounds the cognitive-emotional response. What if we could predict the light response of an individual's pupil, thus creating the opportunity to factor it out of the measurement? In this work, we lay the groundwork for this research by evaluating three models of pupillary light response in 2D, and in a virtual reality (VR) environment. Our results show that either a linear or an exponential model can be fit to an individual participant with an easy-to-use calibration procedure. This work opens several new research directions in VR relating to performance analysis and inspires the use of eye tracking beyond gaze as a pointer and foveated rendering.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3281505.3281538 | VRST |
Keywords | Field | DocType |
Eyetracking, pupil dilation, light response, videos, virtual reality | Computer vision,Pupillary response,Virtual reality,Gaze,Computer science,Pupil,Eye tracking,Artificial intelligence,Rendering (computer graphics),Cognitive load,Brightness | Conference |
ISBN | Citations | PageRank |
978-1-4503-6086-9 | 1 | 0.37 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brendan John | 1 | 1 | 1.05 |
| Pallavi Raiturkar | 2 | 1 | 0.37 |
| Arunava Banerjee | 3 | 313 | 29.18 |
| Eakta Jain | 4 | 88 | 14.60 |