Uncovering and Addressing Blink-Related Challenges in Using Eye Tracking for Interactive Systems

要旨

Currently, interactive systems use physiological sensing to enable advanced functionalities. While eye tracking is a promising means to understand the user, eye tracking data inherently suffers from missing data due to blinks, which may result in reduced system performance. We conducted a literature review to understand how researchers deal with this issue. We uncovered that researchers often implemented their use-case-specific pipeline to overcome the issue, ranging from ignoring missing data to artificial interpolation. With these first insights, we run a large-scale analysis on 11 publicly available datasets to understand the impact of the various approaches on data quality and accuracy. By this, we highlight the pitfalls in data processing and which methods work best. Based on our results, we provide guidelines for handling eye tracking data for interactive systems. Further, we propose a standard data processing pipeline that allows researchers and practitioners to pre-process and standardize their data efficiently.

著者
Jesse W. Grootjen
LMU Munich, Munich, Germany
Henrike Weingärtner
LMU Munich, Munich , Germany
Sven Mayer
LMU Munich, Munich, Germany
論文URL

doi.org/10.1145/3613904.3642086

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Eye and Face

316B
5 件の発表
2024-05-14 18:00:00
2024-05-14 19:20:00