Abstract
Micro-expressions have been shown to be effective in understanding the genuine emotions of a person. While many advances have been made in detecting micro-expressions using deep learning, previous studies in recognizing micro-expressions require pre-processing steps and the use of large feature sets resulting in large runtimes and thus have limited applicability in real-world scenarios. In this paper, we propose time-efficient end-to-end framework which uses landmark-based positional features to generate spatio-temporal graphs that can be applied to micro-expression recognition using Graph Convolutional Neural
Networks (GCNs). We explore the importance of landmark features and propose a selective feature reduction approach to further improve efficiency. We perform experiments using the SMIC, CASMEII and SAMM datasets and demonstrate that our approach significantly speeds up predictions and delivers results
comparable to the state-of-the-art.
Networks (GCNs). We explore the importance of landmark features and propose a selective feature reduction approach to further improve efficiency. We perform experiments using the SMIC, CASMEII and SAMM datasets and demonstrate that our approach significantly speeds up predictions and delivers results
comparable to the state-of-the-art.
Original language | English |
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Title of host publication | 2023 International Conference on Machine Learning and Applications (ICMLA) |
Editors | M. Arif Wani, Mihai Boicu, Moamar Sayed-Mouchaweh, Pedro Henriques Abreu, Joao Gama |
Publisher | IEEE |
Pages | 1-8 |
Number of pages | 8 |
ISBN (Electronic) | 979-8-3503-4534-6 |
ISBN (Print) | 979-8-3503-1891-3 |
DOIs | |
Publication status | Published online - 19 Mar 2024 |
Event | 22nd International Conference on Machine Learning and Applications - Hyatt Regency Jacksonville Riverfront, Florida, United States Duration: 15 Dec 2023 → 17 Dec 2023 https://www.icmla-conference.org/icmla23/ |
Publication series
Name | Proceedings - 22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023 |
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Conference
Conference | 22nd International Conference on Machine Learning and Applications |
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Abbreviated title | ICMLA'23 |
Country/Territory | United States |
City | Florida |
Period | 15/12/23 → 17/12/23 |
Internet address |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- micro-expressions
- emotion
- GCN
- Deep learning
- graph networks
- deep learning