{"title":"An evaluation of pupillary light response models for 2D screens and VR HMDs","authors":"Brendan David-John, Pallavi Raiturkar, Arunava Banerjee, Eakta Jain","doi":"10.1145/3281505.3281538","DOIUrl":null,"url":null,"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.","PeriodicalId":138249,"journal":{"name":"Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3281505.3281538","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
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.