Le, T. T., Tran, T., & Rege, M. (2020). Rank-Pooling-Based Features on Localized Regions for Automatic Micro-Expression Recognition. International Journal of Multimedia Data Engineering and Management (IJMDEM), 11(4), 25-37. doi:10.4018/IJMDEM.2020100102
Rank-pooling-based features on localized regions for automatic micro-expression recognition
|Author:||Le, Trang Thanh Quynh1; Tran, Thuong-Khanh2; Rege, Manjeet1|
1University of St. Thomas, USA
2University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202103036401
|Publish Date:|| 2021-03-03
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.
International journal of multimedia data engineering & management
|Pages:||25 - 37|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
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