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Distinguishing Target and Non-Target Fixations with EEG and Eye Tracking in Realistic Visual Scenes

Published: 04 November 2024 Publication History

Abstract

Distinguishing target from non-target fixations during visual search is a fundamental building block to understand users’ intended actions and to build effective assistance systems. While prior research indicated the feasibility of classifying target vs. non-target fixations based on eye tracking and electroencephalography (EEG) data, these studies were conducted with explicitly instructed search trajectories, abstract visual stimuli, and disregarded any scene context. This is in stark contrast with the fact that human visual search is largely driven by scene characteristics and raises questions regarding generalizability to more realistic scenarios. To close this gap, we, for the first time, investigate the classification of target vs. non-target fixations during free visual search in realistic scenes. In particular, we conducted a 36-participants user study using a large variety of 140 realistic visual search scenes in two highly relevant application scenarios: searching for icons on desktop backgrounds and finding tools in a cluttered workshop. Our approach based on gaze and EEG features outperforms the previous state-of-the-art approach based on a combination of fixation duration and saccade-related potentials. We perform extensive evaluations to assess the generalizability of our approach across scene types. Our approach significantly advances the ability to distinguish between target and non-target fixations in realistic scenarios, achieving 83.6% accuracy in cross-user evaluations. This substantially outperforms previous methods based on saccade-related potentials, which reached only 56.9% accuracy.

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    cover image ACM Other conferences
    ICMI '24: Proceedings of the 26th International Conference on Multimodal Interaction
    November 2024
    725 pages
    ISBN:9798400704628
    DOI:10.1145/3678957
    This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

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    New York, NY, United States

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    Published: 04 November 2024

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    Author Tags

    1. EEG
    2. Eye-tracking
    3. Fixation classification
    4. Visual search

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    • German Ministry for Education and Research (BMBF)

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    ICMI '24
    ICMI '24: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION
    November 4 - 8, 2024
    San Jose, Costa Rica

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    Overall Acceptance Rate 453 of 1,080 submissions, 42%

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