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Exploring the Detection of Spontaneous Recollections during Video-viewing In-the-Wild using Facial Behavior Analysis

Published: 07 November 2022 Publication History

Abstract

Intelligent systems might benefit from automatically detecting when a stimulus has triggered a user’s recollection of personal memories, e.g., to identify that a piece of media content holds personal significance for them. While computational research has demonstrated the potential to identify related states based on facial behavior (e.g., mind-wandering), the automatic detection of spontaneous recollections specifically has not been investigated this far. Motivated by this, we present machine learning experiments exploring the feasibility of detecting whether a video clip has triggered personal memories in a viewer based on the analysis of their Head Rotation, Head Position, Eye Gaze, and Facial Expressions. Concretely, we introduce an approach for automatic detection and evaluate its potential for predictions using in-the-wild webcam recordings. Overall, our findings demonstrate the capacity for above chance detections in both settings, with substantially better performance for the video-independent variant. Beyond this, we investigate the role of person-specific recollection biases for predictions of our video-independent models and the importance of specific modalities of facial behavior. Finally, we discuss the implications of our findings for detecting recollections and user-modeling in adaptive systems.

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    ICMI '22: Proceedings of the 2022 International Conference on Multimodal Interaction
    November 2022
    830 pages
    ISBN:9781450393904
    DOI:10.1145/3536221
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    Published: 07 November 2022

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    Author Tags

    1. Affective Computing
    2. Cognitive Processing
    3. Facial Behavior Analysis
    4. Memories
    5. Mind-Wandering
    6. Recollection
    7. User-Modeling

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