DynGeoNet : fusion network for micro-expression spotting |
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Author: | Tran, Thuong-Khanh1; Vo, Quang-Nhat2; Zhao, Guoying1 |
Organizations: |
1Center for Machine Vision and Signal Analysis, University of Oulu Oulu, Finland 2Silo.AI, Helsinki, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 2.8 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2022012610386 |
Language: | English |
Published: |
Association for Computing Machinery,
2021
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Publish Date: | 2022-01-26 |
Description: |
AbstractMicro-expressions (MEs) are brief and involuntary facial expressions when people hide their true feelings or conceal their emotions. Based on psychology research, MEs play an important role in understanding genuine emotions, which leads to many potential applications. However, the ME analysis system can still not work well in the real environment because of the challenging performance of ME spotting, which is to spot the images with micro-expressions from long video sequences. To improve the performance of ME spotting, we focus on hybrid feature engineering, which aims to create a robust feature for discriminating tiny movements. The proposed framework consists of two main modules: (1) the feature engineering extracts both geometric features and appearance features based on dynamic image; (2) the new deep neural network inputs the handcrafted feature for the late fusion and ME samples classification. Our experimental results from three baseline datasets demonstrate the promising results. see all
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ISBN: | 978-1-4503-8481-0 |
Pages: | 745 - 749 |
DOI: | 10.1145/3462244.3479958 |
OADOI: | https://oadoi.org/10.1145/3462244.3479958 |
Host publication: |
23rd ACM International Conference on Multimodal Interaction, ICMI 2021 |
Conference: |
ACM International Conference on Multimodal Interaction |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
This work was supported by Infotech Oulu, Ministry of Education and Culture of Finland for AI forum project, and Academy of Finland for ICT 2023 project (grant 328115). As well, the authors wish to acknowledge CSC IT Center for Science, Finland, for computational resources. |
Academy of Finland Grant Number: |
328115 |
Detailed Information: |
328115 (Academy of Finland Funding decision) |
Copyright information: |
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