Rank-pooling-based features on localized regions for automatic micro-expression recognition |
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Author: | Le, Trang Thanh Quynh1; Tran, Thuong-Khanh2; Rege, Manjeet1 |
Organizations: |
1University of St. Thomas, USA 2University of Oulu, Finland |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.6 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe202103036401 |
Language: | English |
Published: |
IGI Global,
2020
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Publish Date: | 2021-03-03 |
Description: |
AbstractFacial 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. see all
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Series: |
International journal of multimedia data engineering & management |
ISSN: | 1947-8534 |
ISSN-E: | 1947-8542 |
ISSN-L: | 1947-8534 |
Volume: | 11 |
Issue: | 4 |
Pages: | 25 - 37 |
DOI: | 10.4018/IJMDEM.2020100102 |
OADOI: | https://oadoi.org/10.4018/IJMDEM.2020100102 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Copyright information: |
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