Rank-Pooling-Based Features on Localized Regions for Automatic Micro-Expression Recognition

Trang Thanh Quynh Le, Thuong-Khanh Tran and Manjeet Rege
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Trang Thanh Quynh Le: University of St. Thomas, USA
Thuong-Khanh Tran: University of Oulu, Finland
Manjeet Rege: University of St. Thomas, USA

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2020, vol. 11, issue 4, 25-37

Abstract: Facial micro-expression is a subtle and involuntary facial expression that exhibits short duration and low intensity where hidden feelings can be disclosed. The field of micro-expression analysis has been receiving substantial awareness due to its potential values in a wide variety of practical applications. A number of studies have proposed sophisticated hand-crafted feature representations in order to leverage the task of automatic micro-expression recognition. This paper employs a dynamic image computation method for feature extraction so that features can be learned on certain localized facial regions along with deep convolutional networks to identify micro-expressions presented in the extracted dynamic images. The proposed framework is simple as opposed to other existing frameworks which used complex hand-crafted feature descriptors. For performance evaluation, the framework is tested on three publicly available databases, as well as on the integrated database in which individual databases are merged into a data pool. Impressive results from the series of experimental work show that the technique is promising in recognizing micro-expressions.

Date: 2020
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