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arXiv · 1902.03514

Facial Micro-Expression Spotting and Recognition using Time Contrasted Feature with Visual Memory

Sauradip Nag·Ayan Kumar Bhunia·Aishik Konwer·Partha Pratim Roy
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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.

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Sauradip Nag, Ayan Kumar Bhunia, Aishik Konwer, Partha Pratim Roy. 2019-04-19. Facial Micro-Expression Spotting and Recognition using Time Contrasted Feature with Visual Memory. https://doi.org/10.1109/icassp.2019.8683737

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