CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild
Author(s)
Ding, Li
Terwilliger, Jack
Parab, Aishni
Wang, Meng
Fridman, Lex
Mehler, Bruce
Reimer, Bryan
Date Issued
2023
Journal
ACM Transactions on Computer-Human Interaction
Publisher
ACM
Citation
Ding, Li, Terwilliger, Jack, Parab, Aishni, Wang, Meng, Fridman, Lex et al. 2023. "CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild." ACM Transactions on Computer-Human Interaction.
Version
Final published version
Abstract
Non-intrusive, real-time analysis of the dynamics of the eye region allows us to monitor humans' visual attention allocation and estimate their mental state during the performance of real-world tasks, which can potentially benefit a wide range of human-computer interaction (HCI) applications. While commercial eye-tracking devices have been frequently employed, the difficulty of customizing these devices places unnecessary constraints on the exploration of more efficient, end-to-end models of eye dynamics. In this work, we propose CLERA, a unified model for Cognitive Load and Eye Region Analysis, which achieves precise keypoint detection and spatiotemporal tracking in a joint-learning framework. Our method demonstrates significant efficiency and outperforms prior work on tasks including cognitive load estimation, eye landmark detection, and blink estimation. We also introduce a large-scale dataset of 30k human faces with joint pupil, eye-openness, and landmark annotation, which aims to support future HCI research on human factors and eye-related analysis.
MIT Department
AgeLab (Massachusetts Institute of Technology)
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3603622
