Micro-Expression Recognition Based on Video Motion Magnification and Pre-trained Neural Network

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Abstract

This paper investigates the effects of using video motion magnification methods based on amplitude and phase, respectively, to amplify small facial movements. We hypothesise that this approach will assist in the micro-expression recognition task. To this end, we apply the pre-trained VGGFace2 model with its excellent facial feature capturing ability to transfer learn the magnified micro-expression movement, then encode the spatial information and decode the spatial and temporal information by Bi-LSTM model. Moreover, Grad-CAM is utilised to map the model and visually explain the operating mechanism of the spatio-temporal network. Experiments on the SMIC database confirm that the proposed framework significantly improves the micro-expression recognition rate compared to without video magnification (baseline) and other state-of-the-art methods.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings
EditorsSaif alZahir, Fabrice Labeau, Kenrick Mock
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages549-553
Number of pages5
ISBN (Electronic)9781665441155
ISBN (Print)9781665431026
DOIs
Publication statusPublished - 23 Aug 2021
Event28th IEEE International Conference on Image Processing - Denaʼina Civic and Convention Center, Anchorage, United States
Duration: 19 Sep 202122 Sep 2021
https://2021.ieeeicip.org/

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2021-September
ISSN (Print)1522-4880

Conference

Conference28th IEEE International Conference on Image Processing
Abbreviated titleICIP 2021
Country/TerritoryUnited States
CityAnchorage
Period19/09/2122/09/21
Internet address

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