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Micro-Expression Spotting Based on Optical Flow Feature with Boundary Calibration

Published: 28 October 2024 Publication History

Abstract

Micro-expressions, as a type of facial expression corresponding to macro-expressions, usually have a short duration and low intensity. Due to these characteristics, micro-expression spotting holds significant value in medical care and public safety. Recent years have witnessed advancements in micro-expression spotting methods; however, spotting micro-expressions remains a challenging task due to their brief duration and low intensity. In this paper, we propose a micro-expression spotting method based on optical flow features with boundary calibration. We first perform face detection, cropping, and alignment on images containing faces. Then, regions of interest (ROIs) are defined, and optical flow features are extracted. Furthermore, candidate expression segments are identified based on the magnitude of the processed optical flows. Finally, a boundary calibration module is utilized to calibrate the boundaries. The effectiveness of the proposed method is evaluated on the MEGC2024 test set, resulting in an overall F1-score of 0.27.

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  1. Micro-Expression Spotting Based on Optical Flow Feature with Boundary Calibration

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    cover image ACM Conferences
    MM '24: Proceedings of the 32nd ACM International Conference on Multimedia
    October 2024
    11719 pages
    ISBN:9798400706868
    DOI:10.1145/3664647
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 28 October 2024

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    Author Tags

    1. expression spotting
    2. macro expression
    3. micro expression
    4. optical flow

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    • Research-article

    Funding Sources

    • Beijing Municipal Science & Technology Commission, Administrative Commission of Zhongguancun Science Park
    • Dreams Foundation of Jianghuai Advance Technology Center
    • Natural Science Foundation of China
    • National Aviation Science Foundation

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    MM '24
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    MM '24: The 32nd ACM International Conference on Multimedia
    October 28 - November 1, 2024
    Melbourne VIC, Australia

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    MM '24 Paper Acceptance Rate 1,150 of 4,385 submissions, 26%;
    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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