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Title: Facial Micro-expression Spotting and Recognition Using Time Contrasted Feature with Visual Memory
Authors: Nag S.
Bhunia A.K.
Konwer A.
Pratim Roy, Partha
Published in: Proceedings of ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Abstract: Facial micro-expressions are sudden involuntary minute muscle movements which reveal true emotions that people try to conceal. Spotting a micro-expression and recognizing it is a major challenge owing to its short duration and intensity. Many works pursued traditional and deep learning based approaches to solve this issue but compromised on learning low level features and higher accuracy due to unavailability of datasets. This motivated us to propose a novel joint architecture of spatial and temporal network which extracts time-contrasted features from the feature maps to contrast out micro-expression from rapid muscle movements. The usage of time contrasted features greatly improved the spotting of micro-expression from inconspicuous facial movements. Also, we include a memory module to predict the class and intensity of the micro-expression across the temporal frames of the micro-expression clip. Our method achieves superior performance in comparison to other conventional approaches on CASMEII dataset. © 2019 IEEE.
Citation: Proceedings of ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, (2019), 2022- 2026
Issue Date: 2019
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Facial micro-expression
Optical Flow
Spatial Network
Time contrasted feature
Visual Memory
ISBN: 9.78148E+12
ISSN: 15206149
Author Scopus IDs: 57205431872
Author Affiliations: Nag, S., Kalyani Government Engineering College, India
Bhunia, A.K., Nanyang Technological University, Singapore, Singapore
Konwer, A., Cognizant, India
Roy, P.P., Indian Institute of Technology Roorkee, India
Corresponding Author: Bhunia, A.K.; Nanyang Technological UniversitySingapore; email:
Appears in Collections:Conference Publications [CS]

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